Triple
T250877
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas legislative districts |
E5143
|
entity |
| Predicate | redrawnAfter |
P3336
|
FINISHED |
| Object | decennial United States census |
—
|
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: decennial United States census | Statement: [Texas legislative districts, redrawnAfter, decennial United States census]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: redrawnAfter Context triple: [Texas legislative districts, redrawnAfter, decennial United States census]
-
A.
redesigned
chosen
Indicates that an entity has been modified or created anew in terms of its structure, appearance, or functionality, replacing a previous design.
-
B.
reconstructedAfter
Indicates that one entity has been rebuilt, restored, or reassembled following the occurrence or existence of another entity or event.
-
C.
reconstructedAs
Indicates that one entity has been rebuilt, recreated, or inferred based on evidence, models, or partial information from another entity.
-
D.
paintedEvery
Indicates that an entity applied paint to each and every relevant item in a specified set or domain.
-
E.
reassessedAfter
Indicates that one entity is evaluated or reviewed again at a time point that occurs after another specified event or assessment.
- 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_69a257c4bf688190a46ebbf411ab7473 |
completed | Feb. 28, 2026, 2:49 a.m. |
| NER | Named-entity recognition | batch_69a25d38aba8819081d0958eb60ce27e |
completed | Feb. 28, 2026, 3:12 a.m. |
| PD | Predicate disambiguation | batch_69a25b665f8c8190aac6fcbba2a0eebb |
completed | Feb. 28, 2026, 3:05 a.m. |
Created at: Feb. 28, 2026, 2:54 a.m.