Triple
T1381203
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | S&P Composite 1500 |
E29340
|
entity |
| Predicate | segmentCoverage |
P14568
|
FINISHED |
| Object | large-cap |
—
|
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: large-cap | Statement: [S&P Composite 1500, segmentCoverage, large-cap]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: segmentCoverage Context triple: [S&P Composite 1500, segmentCoverage, large-cap]
-
A.
coverageScope
chosen
Indicates the extent or range of entities, conditions, or situations that are included under a particular coverage or applicability.
-
B.
hasCoverage
Indicates that one entity provides insurance or protection coverage for another entity or subject.
-
C.
isCoveredBy
Indicates that one entity is physically or conceptually overlaid, protected, or enclosed by another entity.
-
D.
regionCoverage
Indicates that one entity geographically spans, includes, or serves the area defined by another entity.
-
E.
numberOfElementsCovered
Indicates the count of distinct elements that are included or encompassed by a given entity or condition.
- 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_69a498d883a48190bfdca525296ef7ee |
completed | March 1, 2026, 7:51 p.m. |
| NER | Named-entity recognition | batch_69a4c31b176c8190a896183140c5c8be |
completed | March 1, 2026, 10:52 p.m. |
| PD | Predicate disambiguation | batch_69a4befe343c81909f758440a531b5be |
completed | March 1, 2026, 10:34 p.m. |
Created at: March 1, 2026, 7:59 p.m.