Triple
T34211432
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | ministerio de defensa |
E877666
|
entity |
| Predicate | tieneSedeTípica |
P93876
|
FINISHED |
| Object | capital del país |
—
|
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: capital del país | Statement: [ministerio de defensa, tieneSedeTípica, capital del país]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tieneSedeTípica Context triple: [ministerio de defensa, tieneSedeTípica, capital del país]
-
A.
tieneSedePrincipal
Indicates that an entity has its main headquarters or principal office located in a specified place.
-
B.
isTypicallyBasedIn
chosen
Indicates that one entity is most commonly located, headquartered, or primarily operates within the context or place specified by another entity.
-
C.
typicalSettlement
Indicates that the subject is a common or characteristic type of settlement typically found in the context of the object.
-
D.
hasBaseOfOperations
Indicates that an entity uses a particular location as its primary place of operation or activity.
-
E.
hasCommercialCenterType
Indicates that an entity has or is associated with a specific type or category of commercial center (e.g., mall, shopping district, business park).
- 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_69f349b0b4bc819088c1552424089ee9 |
completed | April 30, 2026, 12:23 p.m. |
| NER | Named-entity recognition | batch_69f71362f1448190985a80ce7af475cb |
completed | May 3, 2026, 9:20 a.m. |
| PD | Predicate disambiguation | batch_69f7127884388190884f23d181a65d19 |
completed | May 3, 2026, 9:16 a.m. |
Created at: May 1, 2026, 1:55 a.m.