Triple
T14958124
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Miss Hannigan |
E372985
|
entity |
| Predicate | ward |
P21208
|
FINISHED |
| Object |
Tessie
Tessie is one of the young orphan girls in the musical "Annie," known for her anxious personality and frequent cries of "Oh my goodness, oh my goodness!"
|
E1129294
|
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: Tessie | Statement: [Miss Hannigan, ward, Tessie]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Tessie Context triple: [Miss Hannigan, ward, Tessie]
-
A.
Tessie
Tessie is a Boston Red Sox mascot character, often depicted as a green monster and associated with Wally the Green Monster.
-
B.
Tessie Hutchinson
Tessie Hutchinson is the central character in Shirley Jackson’s short story “The Lottery,” known for becoming the scapegoated victim of the town’s brutal annual ritual.
-
C.
Zelma
Zelma is a feminine given name of Hebrew origin, often considered a variant of Selma or Anselma.
-
D.
Melva
Melva is a character in Richard Bruce Nugent’s modernist short story "Smoke, Lilies and Jade," which explores themes of race, sexuality, and artistic identity during the Harlem Renaissance.
-
E.
Mildred
Mildred is the sharp-tongued, loyal housekeeper and assistant to the titular couple in the 1970s television crime drama "McMillan & Wife."
- 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: Tessie Triple: [Miss Hannigan, ward, Tessie]
Generated description
Tessie is one of the young orphan girls in the musical "Annie," known for her anxious personality and frequent cries of "Oh my goodness, oh my goodness!"
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: Tessie Target entity description: Tessie is one of the young orphan girls in the musical "Annie," known for her anxious personality and frequent cries of "Oh my goodness, oh my goodness!"
-
A.
Tessie
Tessie is a Boston Red Sox mascot character, often depicted as a green monster and associated with Wally the Green Monster.
-
B.
Tessie Hutchinson
Tessie Hutchinson is the central character in Shirley Jackson’s short story “The Lottery,” known for becoming the scapegoated victim of the town’s brutal annual ritual.
-
C.
Zelma
Zelma is a feminine given name of Hebrew origin, often considered a variant of Selma or Anselma.
-
D.
Melva
Melva is a character in Richard Bruce Nugent’s modernist short story "Smoke, Lilies and Jade," which explores themes of race, sexuality, and artistic identity during the Harlem Renaissance.
-
E.
Mildred
Mildred is the sharp-tongued, loyal housekeeper and assistant to the titular couple in the 1970s television crime drama "McMillan & Wife."
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded6cd85bc81909040b7ff78f62554 |
completed | April 15, 2026, 12:07 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e9e74fc8190bdd10a25c39829f3 |
completed | May 9, 2026, 12:23 a.m. |
| NEDg | Description generation | batch_69fe83269020819085b904e080578580 |
completed | May 9, 2026, 12:43 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69fe83ccc73881909c28c53052c4cd86 |
completed | May 9, 2026, 12:46 a.m. |
Created at: April 10, 2026, 2:40 a.m.