Triple
T18724865
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gil Elbaz |
E457873
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Factual |
—
|
NE NERFINISHED |
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: Factual | Statement: [Gil Elbaz, employer, Factual]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Factual Context triple: [Gil Elbaz, employer, Factual]
-
A.
Factual
chosen
Factual was a location data company known for providing global places and movement data used in advertising, mobile apps, and analytics.
-
B.
FACT
FACT is the ICAO airport code assigned to Cape Town International Airport in South Africa.
-
C.
Facts
"Facts" is a song by H.E.R. featured on her self-titled compilation album, showcasing her soulful R&B style and introspective lyricism.
-
D.
FACTS
FACTS is the commonly used acronym for the Finnish Academy of Technical Sciences, a learned society that promotes research and expertise in engineering and technology in Finland.
-
E.
The Facts
The Facts is a regional newspaper serving Angleton and the surrounding Brazoria County area in Texas, providing local news, sports, and community coverage.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (2 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_69d8d393ba9c8190a8b03b04ddbb0a09 |
completed | April 10, 2026, 10:40 a.m. |
| NER | Named-entity recognition | batch_69e56d72d2c4819080b0d31860976b5e |
completed | April 20, 2026, 12:04 a.m. |
Created at: April 10, 2026, 11:50 a.m.