Triple
T30025679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tata Sons |
E762873
|
entity |
| Predicate | notableSectorExposure |
P117296
|
FINISHED |
| Object | information technology |
—
|
LITERAL 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: information technology | Statement: [Tata Sons, notableSectorExposure, information technology]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: notableSectorExposure Context triple: [Tata Sons, notableSectorExposure, information technology]
-
A.
notableSector
Indicates that an entity is particularly prominent, influential, or significant within a specified sector or industry.
-
B.
sectorInfluence
Indicates the degree to which one sector affects, shapes, or exerts control over another sector or over outcomes within that sector.
-
C.
sectoralCoverage
Indicates the specific sectors, industries, or domains to which something (such as a policy, agreement, or dataset) applies or extends.
-
D.
notableAssetClass
Indicates that an entity is significantly associated with, or recognized for, a particular class of assets.
-
E.
industryExposure
chosen
Indicates the extent to which an entity is involved in, affected by, or financially linked to a particular industry or set of industries.
- F. None of above.
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_69f2246ee6e48190b69e837b913b398a |
completed | April 29, 2026, 3:31 p.m. |
| NER | Named-entity recognition | batch_6a037c876524819098545e6037d3107d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379e0f3d88190a4ee7b0673f1ef90 |
completed | May 12, 2026, 7:05 p.m. |
Created at: April 29, 2026, 6:48 p.m.