Triple
T7836882
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | John Taylor (Trenton industrialist) |
E181709
|
entity |
| Predicate | productCreated |
P45409
|
FINISHED |
| Object |
Taylor ham
Taylor ham is a seasoned, cured pork product from New Jersey, commonly eaten sliced and fried on breakfast sandwiches, especially in the northern part of the state.
|
E698796
|
NE FINISHED |
How this triple was built (4 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Taylor ham | Statement: [John Taylor (Trenton industrialist), productCreated, Taylor ham]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Taylor ham Context triple: [John Taylor (Trenton industrialist), productCreated, Taylor ham]
-
A.
Taylor
Taylor is a suburban city in Wayne County, Michigan, known for its residential communities and proximity to Detroit.
-
B.
Taylor
Taylor is a common English surname borne by numerous notable individuals across fields such as politics, arts, sports, and academia.
-
C.
Tyler
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
-
D.
Tyler
Tyler is a character in the 2015 horror-thriller film "The Visit," serving as one of the two grandchildren whose unsettling stay with their grandparents drives the movie’s plot.
-
E.
Tyler
Tyler is a fictional character appearing in the American television series "Kristin."
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: Taylor ham Triple: [John Taylor (Trenton industrialist), productCreated, Taylor ham]
Generated description
Taylor ham is a seasoned, cured pork product from New Jersey, commonly eaten sliced and fried on breakfast sandwiches, especially in the northern part of the state.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Taylor ham Target entity description: Taylor ham is a seasoned, cured pork product from New Jersey, commonly eaten sliced and fried on breakfast sandwiches, especially in the northern part of the state.
-
A.
Taylor
Taylor is a suburban city in Wayne County, Michigan, known for its residential communities and proximity to Detroit.
-
B.
Taylor
Taylor is a common English surname borne by numerous notable individuals across fields such as politics, arts, sports, and academia.
-
C.
Tyler
Tyler is the officer in a Masonic lodge responsible for guarding the entrance and ensuring only qualified individuals are admitted to meetings.
-
D.
Tyler
Tyler is a character in the 2015 horror-thriller film "The Visit," serving as one of the two grandchildren whose unsettling stay with their grandparents drives the movie’s plot.
-
E.
Tyler
Tyler is a fictional character appearing in the American television series "Kristin."
- F. None of above. chosen
Provenance (5 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69ca8284a25c8190a1a20afad30da792 |
completed | March 30, 2026, 2:02 p.m. |
| NER | Named-entity recognition | batch_69cb14c203b4819099c039c617628927 |
completed | March 31, 2026, 12:26 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69cb5aad325c8190bced57e8380bc729 |
completed | March 31, 2026, 5:25 a.m. |
| NEDg | Description generation | batch_69cb762dd8348190bf74be4e7f5df1e7 |
completed | March 31, 2026, 7:22 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69cbb24068908190977b266366e5ceea |
completed | March 31, 2026, 11:38 a.m. |
Created at: March 30, 2026, 4:46 p.m.