Triple
T1644647
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Deacon Phillippe |
E35551
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Phillippe |
E207358
|
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: Phillippe | Statement: [Deacon Phillippe, familyName, Phillippe]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Phillippe Context triple: [Deacon Phillippe, familyName, Phillippe]
-
A.
Phillippe
chosen
Phillippe is a given name and surname, typically a French-influenced variant of Philip, used for both real and fictional individuals.
-
B.
Pierre
Pierre is a masculine given name of French origin that has been borne by numerous notable figures in history, arts, and science.
-
C.
Henri
Henri is a given name most famously associated with the French artist Henri Matisse.
-
D.
Édouard
Édouard is the French form of the given name Edward, commonly used in French-speaking countries.
-
E.
Jean-Charles
Jean-Charles is the given name of Jean-Charles Adolphe Alphand, a prominent 19th-century French engineer and landscape architect known for designing many of Paris’s parks and boulevards.
- 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_69a88604618c81908b41f6429c431eb6 |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69aa622e9b08819094960b2329c6e7e6 |
completed | March 6, 2026, 5:12 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69addf308fe4819093ac42f637929a5e |
completed | March 8, 2026, 8:42 p.m. |
Created at: March 4, 2026, 7:28 p.m.