Triple
T1527906
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Texas State Antiquities Landmark |
E32376
|
entity |
| Predicate | appliesPrimarilyTo |
P29843
|
FINISHED |
| Object | publicly owned properties |
—
|
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: publicly owned properties | Statement: [Texas State Antiquities Landmark, appliesPrimarilyTo, publicly owned properties]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: appliesPrimarilyTo Context triple: [Texas State Antiquities Landmark, appliesPrimarilyTo, publicly owned properties]
-
A.
appliesTo
Indicates that something is relevant, valid, or has effect in relation to a particular entity, case, or context.
-
B.
usedPrimarilyIn
Indicates that something is mainly or most commonly employed within a particular context, domain, or purpose.
-
C.
appliesToPerson
Indicates that something (such as a rule, condition, or attribute) is relevant or applicable to a specific person.
-
D.
usedOn
Indicates that one entity is applied to, operated on, or otherwise utilized in relation to another entity.
-
E.
appliesAt
Indicates that an action, rule, or condition is relevant to or in effect at a specific location, context, or point in time.
- 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_69a885e9b0ac819093a9806ad0efc82c |
completed | March 4, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69a933ddc5a881909cdf503f2bc29bd4 |
completed | March 5, 2026, 7:42 a.m. |
| PD | Predicate disambiguation | batch_69a907ae8f688190ad9000ea1e018585 |
completed | March 5, 2026, 4:33 a.m. |
| PDg | Predicate description generation | batch_69a933dce3488190b20f0e3d37d16371 |
completed | March 5, 2026, 7:42 a.m. |
Created at: March 4, 2026, 7:26 p.m.