Triple
T20764293
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Sullivan’s Snack Stand |
E511053
|
entity |
| Predicate | alternateName |
P39
|
FINISHED |
| Object |
Sullivan’s
Sullivan’s is a casual snack stand known for serving quick, beach-style fare and refreshments.
|
E1449879
|
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: Sullivan’s | Statement: [Sullivan’s Snack Stand, alternateName, Sullivan’s]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Sullivan’s Context triple: [Sullivan’s Snack Stand, alternateName, Sullivan’s]
-
A.
Sullivan
Sullivan is a common Irish surname that has been borne by numerous notable figures in politics, arts, sports, and other fields.
-
B.
Sullivan
Sullivan is a shortened name for the international law firm Sullivan & Worcester LLP, known for its corporate, tax, and financial legal services.
-
C.
Sullivan
Sullivan is a town in Madison County, New York, known for its rural character and proximity to Chittenango and Oneida Lake.
-
D.
Sullivan & Son
Sullivan & Son is an American sitcom that follows a corporate lawyer who leaves his big-city career to run his family's bar in a working-class Pittsburgh neighborhood.
-
E.
Sylvia’s Restaurant
Sylvia’s Restaurant is a famed soul food eatery in Harlem, New York City, celebrated as a cultural institution and gathering place for locals, celebrities, and politicians alike.
- 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: Sullivan’s Triple: [Sullivan’s Snack Stand, alternateName, Sullivan’s]
Generated description
Sullivan’s is a casual snack stand known for serving quick, beach-style fare and refreshments.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Sullivan’s Target entity description: Sullivan’s is a casual snack stand known for serving quick, beach-style fare and refreshments.
-
A.
Sullivan
Sullivan is a common Irish surname that has been borne by numerous notable figures in politics, arts, sports, and other fields.
-
B.
Sullivan
Sullivan is a shortened name for the international law firm Sullivan & Worcester LLP, known for its corporate, tax, and financial legal services.
-
C.
Sullivan
Sullivan is a town in Madison County, New York, known for its rural character and proximity to Chittenango and Oneida Lake.
-
D.
Sullivan & Son
Sullivan & Son is an American sitcom that follows a corporate lawyer who leaves his big-city career to run his family's bar in a working-class Pittsburgh neighborhood.
-
E.
Sylvia’s Restaurant
Sylvia’s Restaurant is a famed soul food eatery in Harlem, New York City, celebrated as a cultural institution and gathering place for locals, celebrities, and politicians alike.
- 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_69e0b4ca01148190ac018e57e0cab46f |
completed | April 16, 2026, 10:07 a.m. |
| NER | Named-entity recognition | batch_69e6c24b18b8819082e61104be6f83a3 |
completed | April 21, 2026, 12:18 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_6a08ef893de48190811d4d34296ce34d |
completed | May 16, 2026, 10:28 p.m. |
| NEDg | Description generation | batch_6a08f34a218c81909fe2573f4549411c |
completed | May 16, 2026, 10:44 p.m. |
| NED2 | Entity disambiguation (via description) | batch_6a08f3fc2ec88190a7a7eed11d51ec8e |
completed | May 16, 2026, 10:47 p.m. |
Created at: April 16, 2026, 12:36 p.m.