Triple
T5577213
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Athena Grant |
E146348
|
entity |
| Predicate | child |
P120
|
FINISHED |
| Object |
May Grant
May Grant is a fictional character from the television series "9-1-1," known as the daughter of LAPD Sergeant Athena Grant.
|
E536170
|
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: May Grant | Statement: [Athena Grant, child, May Grant]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: May Grant Context triple: [Athena Grant, child, May Grant]
-
A.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
B.
Miriam Grant
Miriam Grant was a 19th-century American woman best known as a member of the prominent Grant family, being the granddaughter of U.S. President Ulysses S. Grant.
-
C.
Anne Ashmond
Anne Ashmond is a fictional character appearing in the film "Royal Wedding."
-
D.
Jane Greenwood
Jane Greenwood is a renowned British-American costume designer celebrated for her extensive work in theatre, opera, and television, including numerous Broadway productions and award-winning designs.
-
E.
Susannah Grant
Susannah Grant is an American screenwriter, director, and producer best known for writing the film "Erin Brockovich" and creating several television series.
- 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: May Grant Triple: [Athena Grant, child, May Grant]
Generated description
May Grant is a fictional character from the television series "9-1-1," known as the daughter of LAPD Sergeant Athena Grant.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: May Grant Target entity description: May Grant is a fictional character from the television series "9-1-1," known as the daughter of LAPD Sergeant Athena Grant.
-
A.
Jennifer Grant
Jennifer Grant is an American actress and the daughter of classic Hollywood film star Cary Grant.
-
B.
Miriam Grant
Miriam Grant was a 19th-century American woman best known as a member of the prominent Grant family, being the granddaughter of U.S. President Ulysses S. Grant.
-
C.
Anne Ashmond
Anne Ashmond is a fictional character appearing in the film "Royal Wedding."
-
D.
Jane Greenwood
Jane Greenwood is a renowned British-American costume designer celebrated for her extensive work in theatre, opera, and television, including numerous Broadway productions and award-winning designs.
-
E.
Susannah Grant
Susannah Grant is an American screenwriter, director, and producer best known for writing the film "Erin Brockovich" and creating several television series.
- 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_69c008ffed108190a084602227af6157 |
completed | March 22, 2026, 3:21 p.m. |
| NER | Named-entity recognition | batch_69c020697fbc8190bd084d7896db3ab8 |
completed | March 22, 2026, 5:01 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c04d21ac6c81908a07c049d1ab81c6 |
completed | March 22, 2026, 8:12 p.m. |
| NEDg | Description generation | batch_69c04e879a8c8190942968982223f6e4 |
completed | March 22, 2026, 8:18 p.m. |
| NED2 | Entity disambiguation (via description) | batch_69c04f3c31b48190aeefd41bea55d367 |
completed | March 22, 2026, 8:21 p.m. |
Created at: March 22, 2026, 3:37 p.m.