Triple
T9743892
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Viswanathan Anand |
E236257
|
entity |
| Predicate | sponsor |
P67
|
FINISHED |
| Object |
TVH
TVH is an Indian real estate and infrastructure development company known for sponsoring chess legend Viswanathan Anand.
|
E817799
|
NE FINISHED |
How this triple was built (4 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: TVH | Statement: [Viswanathan Anand, sponsor, TVH]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: TVH Context triple: [Viswanathan Anand, sponsor, TVH]
-
A.
TVING
TVING is a South Korean online streaming platform offering a wide range of domestic films, dramas, and entertainment content.
-
B.
We TV
We TV is an American cable television network known for its reality programming focused on relationships, family life, and pop culture.
-
C.
TVF
TVF is the ICAO airline designator used for Transavia France, a French low-cost carrier.
-
D.
.tv
.tv is the country-code top-level domain originally assigned to Tuvalu that has become popular worldwide for websites related to television and video content.
-
E.
TVS Television Network
TVS Television Network was an American syndicated sports television network known for broadcasting a wide range of live sporting events and special programming from the 1960s through the 1980s.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: TVH Triple: [Viswanathan Anand, sponsor, TVH]
Generated description
TVH is an Indian real estate and infrastructure development company known for sponsoring chess legend Viswanathan Anand.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: TVH Target entity description: TVH is an Indian real estate and infrastructure development company known for sponsoring chess legend Viswanathan Anand.
-
A.
TVING
TVING is a South Korean online streaming platform offering a wide range of domestic films, dramas, and entertainment content.
-
B.
We TV
We TV is an American cable television network known for its reality programming focused on relationships, family life, and pop culture.
-
C.
TVF
TVF is the ICAO airline designator used for Transavia France, a French low-cost carrier.
-
D.
.tv
.tv is the country-code top-level domain originally assigned to Tuvalu that has become popular worldwide for websites related to television and video content.
-
E.
TVS Television Network
TVS Television Network was an American syndicated sports television network known for broadcasting a wide range of live sporting events and special programming from the 1960s through the 1980s.
- F. None of above. chosen
Provenance (5 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_69ca84d3e24481908a476e2231123cf9 |
completed | March 30, 2026, 2:12 p.m. |
| NER | Named-entity recognition | batch_69cd9f2e5bb081908047e3bf5fe3991c |
completed | April 1, 2026, 10:41 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69d1affb761881908dde9a4f028c32f6 |
completed | April 5, 2026, 12:42 a.m. |
| NEDg | Description generation | batch_69d1b0f7a68481909de080dd78f883a8 |
completed | April 5, 2026, 12:46 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69d1b17bd97c8190b77815db5a6a70d9 |
completed | April 5, 2026, 12:49 a.m. |
Created at: March 30, 2026, 8:23 p.m.