Triple
T5781665
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | America/Chicago |
E127571
|
entity |
| Predicate | hasHistoricalChanges |
P21515
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [America/Chicago, hasHistoricalChanges, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHistoricalChanges Context triple: [America/Chicago, hasHistoricalChanges, true]
-
A.
includesChangeHistory
chosen
Indicates that the subject maintains or contains a record of past modifications or changes made to it.
-
B.
hasHistorySince
Indicates that an entity has maintained a particular state, condition, or relationship continuously starting from a specified point in time.
-
C.
hasHistoricalShiftFrom
Indicates a relationship where one state, practice, or condition has been replaced or transformed over time from another earlier state, practice, or condition.
-
D.
hasTypeHistory
Indicates that an entity is associated with a record or sequence of its past and present types or classifications over time.
-
E.
hasHistoricalShiftTo
Indicates a change over time in which one state, condition, or configuration is replaced or transformed into another in a historically traceable way.
- 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_69c008361fa88190aefa4dc41b051e7f |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c02a17315881908aa12a830ba5f22b |
completed | March 22, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69c021d2cd608190b98a7e3aa7001d27 |
completed | March 22, 2026, 5:07 p.m. |
Created at: March 22, 2026, 3:50 p.m.