Triple
T11356893
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Juliette Fontaine |
E268976
|
entity |
| Predicate | keyRelationship |
P26456
|
FINISHED |
| Object | develops bond with Michel |
E427344
|
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: develops bond with Michel | Statement: [Juliette Fontaine, keyRelationship, develops bond with Michel]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: develops bond with Michel Context triple: [Juliette Fontaine, keyRelationship, develops bond with Michel]
-
A.
Michaël
Michaël is a given name, typically a French or Dutch variant of the name Michael, used for males in various European countries.
-
B.
Michel
chosen
Michel is a fictional character appearing in Frederick Forsyth’s political thriller novel "The Dogs of War."
-
C.
Michel
Michel is the birth name of the acclaimed Egyptian actor Omar Sharif, renowned for his roles in classic films such as "Lawrence of Arabia" and "Doctor Zhivago."
-
D.
Michel
Michel is a French given name commonly used for males, equivalent to "Michael" in English.
-
E.
Misha
Misha is the bear mascot of the 1980 Moscow Summer Olympics, widely remembered for its iconic, sentimental farewell during the closing ceremony.
- 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_69d6aacbe18081909e5fadb50082dd96 |
completed | April 8, 2026, 7:21 p.m. |
| NER | Named-entity recognition | batch_69d7ea419afc8190b3a93141d015ebdf |
completed | April 9, 2026, 6:04 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e543b3cbd88190bb479ac88f8ca710 |
completed | April 19, 2026, 9:05 p.m. |
Created at: April 8, 2026, 9:33 p.m.