Triple
T793010
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | NYSE Composite |
E16955
|
entity |
| Predicate | hasComponentCount |
P19198
|
FINISHED |
| Object | over 2000 issues |
—
|
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: over 2000 issues | Statement: [NYSE Composite, hasComponentCount, over 2000 issues]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasComponentCount Context triple: [NYSE Composite, hasComponentCount, over 2000 issues]
-
A.
hasComponentGroup
Indicates that an entity includes or is associated with a specific group of components treated as a single unit.
-
B.
hasMemberCountType
Indicates the type or classification used to describe how the number of members in a group or collection is represented.
-
C.
hasMajorComponent
Indicates that one entity includes another entity as a primary or most significant component or part.
-
D.
hasSectionCount
Indicates that an entity is associated with a specific number of sections it contains or comprises.
-
E.
hasServerComponent
Indicates that an entity includes, depends on, or is associated with a particular server-side component.
- 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_69a4936cb7448190914f5fe4b8d81607 |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a4a79a3bbc81908d818c50a366b0f8 |
completed | March 1, 2026, 8:54 p.m. |
| PD | Predicate disambiguation | batch_69a4a510f61881909175d6d8719246cd |
completed | March 1, 2026, 8:44 p.m. |
| PDg | Predicate description generation | batch_69a4a5edd0248190bd0240e5b3e67c71 |
completed | March 1, 2026, 8:47 p.m. |
Created at: March 1, 2026, 7:38 p.m.