Triple
T10845838
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | L110 |
E256006
|
entity |
| Predicate | usedOn |
P2367
|
FINISHED |
| Object | LVM3 |
E238215
|
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: LVM3 | Statement: [L110, usedOn, LVM3]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: LVM3 Context triple: [L110, usedOn, LVM3]
-
A.
LVM3
chosen
LVM3 is India’s heavy-lift launch vehicle developed by ISRO to carry large communication and deep-space satellites into orbit.
-
B.
ML3
ML3 is a UK postcode district covering part of Hamilton and surrounding areas in South Lanarkshire, Scotland.
-
C.
LVS
LVS is the stock ticker symbol for Las Vegas Sands Corp., a major global developer and operator of casino resorts and integrated entertainment properties.
-
D.
ML-3
ML-3 is one of Pakistan Railways’ main railway corridors, serving as a key route that supports regional connectivity and freight and passenger movement within the country.
-
E.
UPVM3
UPVM3 is a French public university in Montpellier specializing in arts, humanities, and social sciences, named after the writer and philosopher Paul Valéry.
- 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_69d6aa81a5d08190aa86689061d1ddd2 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d750d132e081909c977b3dc4110ca4 |
completed | April 9, 2026, 7:10 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69e154b2eb08819080a9905dbf378111 |
completed | April 16, 2026, 9:29 p.m. |
Created at: April 8, 2026, 9:19 p.m.