Triple
T35212333
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lord of Villalba and its land |
E1016717
|
entity |
| Predicate | titleHolderObligations |
P199964
|
FINISHED |
| Object | defense of the territory |
—
|
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: defense of the territory | Statement: [Lord of Villalba and its land, titleHolderObligations, defense of the territory]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: titleHolderObligations Context triple: [Lord of Villalba and its land, titleHolderObligations, defense of the territory]
-
A.
titleHolderRepresents
Indicates that a title holder serves as a representative or proxy for another party in relation to that title.
-
B.
titleHolderSee
Indicates that one who holds a title or position observes, meets, or has an in-person encounter with another entity.
-
C.
titleHolderIs
Indicates that one entity currently holds or possesses a specific title associated with another entity.
-
D.
titleHolderType
Indicates the specific role or capacity in which an entity holds a title (e.g., owner, trustee, beneficiary).
-
E.
titleHolderRelationship
Indicates a relationship where one entity holds, possesses, or bears a specific title in connection to another entity or context.
- 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_69f76ddf549c8190869d0af076fd2c28 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff65987ff88190b09be64f7c0e1da9 |
completed | May 9, 2026, 4:49 p.m. |
| PD | Predicate disambiguation | batch_69ff6525b0548190bef7a9f009e00bb8 |
completed | May 9, 2026, 4:47 p.m. |
| PDg | Predicate description generation | batch_69ff659717708190bb56714d1b261063 |
completed | May 9, 2026, 4:49 p.m. |
Created at: May 3, 2026, 4:02 p.m.