Triple
T17377090
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | IndyCar Classic |
E422466
|
entity |
| Predicate | sponsoredBy |
P67
|
FINISHED |
| Object | NTT |
—
|
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: NTT | Statement: [IndyCar Classic, sponsoredBy, NTT]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: NTT Context triple: [IndyCar Classic, sponsoredBy, NTT]
-
A.
NTT
NTT is a 3.58-meter optical telescope operated by the European Southern Observatory at La Silla Observatory in Chile, notable for pioneering active optics technology.
-
B.
NTT
NTT is the commonly used abbreviation for East Nusa Tenggara, a province in eastern Indonesia known for its rugged islands, diverse cultures, and destinations like Komodo National Park.
-
C.
NTT
chosen
NTT is a major Japanese telecommunications and technology services company known for its global IT solutions and network infrastructure.
-
D.
NTT DoCoMo
NTT DoCoMo is Japan’s largest mobile network operator, known for pioneering advanced mobile technologies and services, including early 3G deployments.
-
E.
KDDI
KDDI is a major Japanese telecommunications company that provides mobile, broadband, and other communication services domestically and internationally.
- 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_69d889d6535c81908be333c01deaec4e |
completed | April 10, 2026, 5:25 a.m. |
| NER | Named-entity recognition | batch_69e43a6ddbd081908908b953597977d2 |
completed | April 19, 2026, 2:14 a.m. |
Created at: April 10, 2026, 5:45 a.m.