Triple
T11444119
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Larsen & Toubro |
E271219
|
entity |
| Predicate | shortName |
P43
|
FINISHED |
| Object | L&T |
E271219
|
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: L&T | Statement: [Larsen & Toubro, shortName, L&T]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: L&T Context triple: [Larsen & Toubro, shortName, L&T]
-
A.
Larsen & Toubro
chosen
Larsen & Toubro is a major Indian multinational conglomerate known for its leadership in engineering, construction, manufacturing, and technology services.
-
B.
Wipro Limited
Wipro Limited is a major Indian multinational information technology, consulting, and business process services company headquartered in Bengaluru.
-
C.
Birla Corporation Limited
Birla Corporation Limited is a major Indian conglomerate company of the Birla family, primarily known for its cement and building materials business along with diversified industrial interests.
-
D.
Reliance Industries Limited
Reliance Industries Limited is a major Indian multinational conglomerate with leading businesses in energy, petrochemicals, retail, and telecommunications.
-
E.
Tata Group
Tata Group is a major Indian multinational conglomerate with diverse businesses spanning sectors such as steel, automobiles, information technology, telecommunications, and hospitality.
- 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_69d6aadff8888190a13f253f0d460874 |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8088a66f48190b2b4a56cd62097cf |
completed | April 9, 2026, 8:14 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e5d3afe7fc8190acc8c803ff5efe5a |
completed | April 20, 2026, 7:20 a.m. |
Created at: April 8, 2026, 9:35 p.m.