Triple
T723729
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | XNYS |
E14673
|
entity |
| Predicate | identificationScope |
P18655
|
FINISHED |
| Object | trading venue |
—
|
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: trading venue | Statement: [XNYS, identificationScope, trading venue]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: identificationScope Context triple: [XNYS, identificationScope, trading venue]
-
A.
identifierFor
Indicates that one entity serves as a unique identifying label or code for another entity.
-
B.
identificationRole
Indicates that an entity serves as an identifier or plays a role in uniquely distinguishing or recognizing another entity.
-
C.
organizationalScope
Indicates the range or extent of responsibility, authority, or applicability that an action, policy, or relationship has within an organization or its sub-units.
-
D.
identityConcept
Indicates that two concepts are the same in identity, representing exactly the same underlying idea or meaning.
-
E.
locationScope
Indicates the specific geographic or spatial area within which a given relationship, condition, or action is considered valid or applicable.
- F. None of above. chosen
Provenance (4 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_69a4934c753c81909b309027e48b9b3a |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a5a5360c8190b16e1e4f4206d0aa |
completed | March 1, 2026, 8:46 p.m. |
| PD | Predicate disambiguation | batch_69a4a4f700cc81908c6de3eedf68433c |
completed | March 1, 2026, 8:43 p.m. |
| PDg | Predicate description generation | batch_69a4a55a26e081908134ee93faaf7c40 |
completed | March 1, 2026, 8:45 p.m. |
Created at: March 1, 2026, 7:37 p.m.