Triple
T6498909
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lawrence Harvey Zeiger |
E148828
|
entity |
| Predicate | employer |
P7
|
FINISHED |
| Object | Ora TV |
E54275
|
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: Ora TV | Statement: [Lawrence Harvey Zeiger, employer, Ora TV]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Ora TV Context triple: [Lawrence Harvey Zeiger, employer, Ora TV]
-
A.
Ora TV
chosen
Ora TV is a digital television network and production company co-founded by Larry King that creates and distributes original online video programming.
-
B.
Orange TV
Orange TV is a subscription-based television platform operated by the telecommunications company Orange, offering a range of live channels and on-demand content.
-
C.
Star TV
Star TV is a major Asian satellite television network known for its broad entertainment and news programming across multiple countries.
-
D.
Antenna TV
Antenna TV is an American digital multicast television network that primarily airs classic television series from the 1950s through the early 2000s.
-
E.
Estrella TV
Estrella TV is a Spanish-language American broadcast television network known for its variety of entertainment programming targeting Hispanic audiences in the United States.
- 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_69c687e9ad288190bae5bcac9c8ac855 |
completed | March 27, 2026, 1:36 p.m. |
| NER | Named-entity recognition | batch_69c68ad00d10819096c43f311388fa3a |
completed | March 27, 2026, 1:49 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69c6cb16d6a48190b6871e55fda2e1a6 |
completed | March 27, 2026, 6:23 p.m. |
Created at: March 27, 2026, 1:41 p.m.