Triple
T14945730
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hannah Heloise Trimble Durant |
E372651
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Heloise |
E645649
|
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: Heloise | Statement: [Hannah Heloise Trimble Durant, givenName, Heloise]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Heloise Context triple: [Hannah Heloise Trimble Durant, givenName, Heloise]
-
A.
Héloïse
chosen
Héloïse was a 12th-century French scholar and abbess renowned for her tragic love affair and celebrated correspondence with the philosopher Peter Abelard.
-
B.
Isabelle
Isabelle is a feminine given name of French origin, commonly used in many countries and cultures.
-
C.
Isabelle
Isabelle is a popular character from the Animal Crossing series who also appears as a playable racer in Mario Kart 8.
-
D.
Isabelle
Isabelle is a prominent interactive theorem prover and proof assistant widely used in formal verification and mathematical logic research.
-
E.
Honorine
Honorine is a feminine given name of French origin, used both as a standalone first name and as part of compound names.
- 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_69d85cca979481908747d2a81eba1cea |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69ded68d20048190a403af85fe43dede |
completed | April 15, 2026, 12:06 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fe7e963c548190b3a06ffbbb3298b2 |
completed | May 9, 2026, 12:23 a.m. |
Created at: April 10, 2026, 2:39 a.m.