Triple
T6581692
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | SPY |
E157309
|
entity |
| Predicate | geographicExposure |
P23750
|
FINISHED |
| Object | United States equities |
—
|
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: United States equities | Statement: [SPY, geographicExposure, United States equities]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: geographicExposure Context triple: [SPY, geographicExposure, United States equities]
-
A.
regionExposure
chosen
Indicates that an entity is subject to or affected by exposure within a specific geographic or spatial region.
-
B.
geographicContext
Indicates that one entity is situated within, associated with, or characterized by the geographic setting or region defined by another entity.
-
C.
geographicDiversityRequirement
Indicates a requirement that entities involved must be distributed across different geographic areas or locations rather than concentrated in a single place.
-
D.
geographicAreaOfSupport
Indicates the geographic region or area within which support, assistance, or services are provided or applicable.
-
E.
impactRegion
Indicates the geographic or spatial area that is affected or influenced by a particular event, action, or phenomenon.
- 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_69c6882b3a108190b3a9eb343ae4162c |
completed | March 27, 2026, 1:37 p.m. |
| NER | Named-entity recognition | batch_69c6c07cdf048190945ca5810fb1de88 |
completed | March 27, 2026, 5:38 p.m. |
| PD | Predicate disambiguation | batch_69c6acfb462481909cb7aff5af4bca9d |
completed | March 27, 2026, 4:14 p.m. |
Created at: March 27, 2026, 1:54 p.m.