Triple
T10525138
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannah Weinstein |
E248281
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Hannah |
E367987
|
NE FINISHED |
How this triple was built (2 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: Hannah | Statement: [Hannah Weinstein, givenName, Hannah]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Hannah Context triple: [Hannah Weinstein, givenName, Hannah]
-
A.
Hannah
Hannah is a biblical figure in the Book of 1 Samuel known for her fervent prayer for a child and as the mother of the prophet Samuel.
-
B.
Hannah
Hannah is a person associated in some way with the city of Santa Ana, California.
-
C.
Hannah
Hannah is the introspective, commitment-averse young woman at the center of the mumblecore film "Hannah Takes the Stairs," whose romantic indecision drives the movie’s exploration of twentysomething relationships.
-
D.
Hannah
Hannah is a key ally of Commander Schultz, likely playing an important supportive or collaborative role in his missions or objectives.
-
E.
Hannah
chosen
Hannah is an alternate given name associated with American actress Dakota Fanning, whose full name is Hannah Dakota Fanning.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 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_69d381c5c7448190bec34bee7ec72bac |
completed | April 6, 2026, 9:49 a.m. |
| NER | Named-entity recognition | batch_69d509f4020c8190b78c49da086df757 |
completed | April 7, 2026, 1:43 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d90e26c4908190b77d73c11bee6119 |
completed | April 10, 2026, 2:50 p.m. |
Created at: April 6, 2026, 12:29 p.m.