Triple
T2435143
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Branch v. Texas |
E52941
|
entity |
| Predicate | postFurman |
P39290
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Branch v. Texas, postFurman, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: postFurman Context triple: [Branch v. Texas, postFurman, yes]
-
A.
formerCampus
Indicates that an entity was once located on or associated with a particular campus, but is no longer based there.
-
B.
campus
Indicates that an entity is located on, associated with, or taking place within a particular campus.
-
C.
sisterCampus
Indicates that two educational institutions are formally recognized as sister campuses, typically sharing an affiliation, governance, or coordinated programs while remaining distinct entities.
-
D.
postTown
Indicates the town or locality that serves as the postal address destination for a given address or location.
-
E.
otherMainCampus
Indicates that an institution has an additional primary campus distinct from its main campus.
- 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_69ab4959bcc0819083246f9fb10439e3 |
completed | March 6, 2026, 9:38 p.m. |
| NER | Named-entity recognition | batch_69abcebf7cac8190889e6890d72c256c |
completed | March 7, 2026, 7:07 a.m. |
| PD | Predicate disambiguation | batch_69abc5ac11b081908ce6a506e81a742a |
completed | March 7, 2026, 6:29 a.m. |
| PDg | Predicate description generation | batch_69abcebe7dd08190b197a2a0e78787e3 |
completed | March 7, 2026, 7:07 a.m. |
Created at: March 6, 2026, 9:43 p.m.