Triple
T12451769
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UL |
E297548
|
entity |
| Predicate | underlyingCompanyOwnsBrand |
P6745
|
FINISHED |
| Object | Cif |
E297565
|
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: Cif | Statement: [UL, underlyingCompanyOwnsBrand, Cif]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Cif Context triple: [UL, underlyingCompanyOwnsBrand, Cif]
-
A.
Cif
chosen
Cif is a household cleaning product brand known for its creams and sprays used to remove tough dirt and stains from various surfaces.
-
B.
CIF
CIF is the governing body for high school sports and athletic competitions in the state of California.
-
C.
CIF2
CIF2 is an updated version of the Crystallographic Information Framework standard designed to more robustly and flexibly represent crystallographic data.
-
D.
CIF1
CIF1 is the original version of the Crystallographic Information File standard used to represent and exchange crystallographic data in a structured text format.
-
E.
Cito
Cito is a former Major League Baseball outfielder and manager best known for leading the Toronto Blue Jays to back-to-back World Series championships in 1992 and 1993.
- 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_69d6ada166c48190b902972cd2408fa3 |
completed | April 8, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69d9541ace208190a5149b6f18fa196d |
completed | April 10, 2026, 7:48 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69f64b9f4dd08190b1d62b03d68cc8a6 |
completed | May 2, 2026, 7:08 p.m. |
Created at: April 8, 2026, 9:56 p.m.