Triple
T58135
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guaranteed Rate Field |
E1150
|
entity |
| Predicate | hasTenantSince |
P3320
|
FINISHED |
| Object | Chicago White Sox, 1991 |
—
|
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: Chicago White Sox, 1991 | Statement: [Guaranteed Rate Field, hasTenantSince, Chicago White Sox, 1991]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTenantSince Context triple: [Guaranteed Rate Field, hasTenantSince, Chicago White Sox, 1991]
-
A.
hasUserService
Indicates that an entity is associated with or utilizes a particular user-related service.
-
B.
usedAt
Indicates that something is employed, applied, or utilized at a particular place, time, or context.
-
C.
hasAccessTo
Indicates that one entity is permitted to enter, use, or interact with another entity, resource, or location.
-
D.
usedSinceCentury
Indicates that something has been in use starting from a specified century.
-
E.
hasAge
Indicates that an entity possesses a specific age value, typically expressed as a number of time units since its birth or creation.
- 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_69a248adc5b48190aa8db9fb092fb28a |
completed | Feb. 28, 2026, 1:45 a.m. |
| NER | Named-entity recognition | batch_69a24c9057348190aa6692eeeae19569 |
completed | Feb. 28, 2026, 2:01 a.m. |
| PD | Predicate disambiguation | batch_69a24ac7547c81909bb68f327cdb9158 |
completed | Feb. 28, 2026, 1:54 a.m. |
| PDg | Predicate description generation | batch_69a24c8fa20c8190aacc38e53d1f654c |
completed | Feb. 28, 2026, 2:01 a.m. |
Created at: Feb. 28, 2026, 1:50 a.m.