Triple
T13871212
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Serge Ibaka |
E333453
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Serge |
E326747
|
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: Serge | Statement: [Serge Ibaka, givenName, Serge]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Serge Context triple: [Serge Ibaka, givenName, Serge]
-
A.
Serge
chosen
Serge is a masculine given name of French origin, commonly used in Francophone countries and derived from the Latin name Sergius.
-
B.
Serge July
Serge July is a French journalist and media executive best known for co-founding and long directing the left-leaning daily newspaper Libération.
-
C.
Sergei
Sergei is a masculine given name of Slavic origin, commonly used in Russia and other Eastern European countries.
-
D.
Sergeant Kourov
Sergeant Kourov is a Soviet military non-commissioned officer character best known as an associate of Colonel Zaysen in the film "Rambo III."
-
E.
Sergy
Sergy is a small commune in the Ain department of eastern France, located near the Swiss border in the Pays de Gex region.
- 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_69d81c5ced9c8190b0e9bcc6effe5959 |
completed | April 9, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69de05c638248190bbe5d19f7b88d0f9 |
completed | April 14, 2026, 9:15 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f7c107c20c81909dff0ca4a59fcc55 |
completed | May 3, 2026, 9:41 p.m. |
Created at: April 9, 2026, 10:14 p.m.