Triple
T14156170
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Pierre Veber |
E350818
|
entity |
| Predicate | familyName |
P18
|
FINISHED |
| Object | Veber |
E885603
|
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: Veber | Statement: [Pierre Veber, familyName, Veber]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Veber Context triple: [Pierre Veber, familyName, Veber]
-
A.
Veber
chosen
Veber is a French surname most notably associated with filmmaker and playwright Francis Veber.
-
B.
Stavenhagen
Stavenhagen is a small town in northeastern Germany known for its historical architecture and its association with the writer Fritz Reuter.
-
C.
Zerbe
Zerbe is a surname of German origin borne by various notable individuals, including American actor Anthony Zerbe.
-
D.
Erving
Erving is the surname of Julius Erving, the Hall of Fame American basketball player widely known as "Dr. J."
-
E.
Regardie
Regardie is the surname of Israel Regardie, a prominent 20th-century occultist and author associated with the Hermetic Order of the Golden Dawn.
- 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_69d8278775fc8190b0802d22ca2f495d |
completed | April 9, 2026, 10:26 p.m. |
| NER | Named-entity recognition | batch_69de6135744c81909a43d659f5fe2895 |
completed | April 14, 2026, 3:45 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69fcf7ec6448819087e50aac964ec637 |
completed | May 7, 2026, 8:37 p.m. |
Created at: April 10, 2026, 12:58 a.m.