Triple
T1998534
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Siete Leyes |
E43411
|
entity |
| Predicate | territorialDivision |
P18247
|
FINISHED |
| Object | departments |
—
|
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: departments | Statement: [Siete Leyes, territorialDivision, departments]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: territorialDivision Context triple: [Siete Leyes, territorialDivision, departments]
-
A.
politicalDivision
Indicates that one entity is a governmental or administrative subdivision or jurisdiction within the territory or authority of another entity.
-
B.
partitionedTerritory
chosen
Indicates that a larger territory has been divided into distinct parts or regions, typically with defined boundaries or administrative separation.
-
C.
countrySubdivision
Indicates that one geopolitical region is an administrative or territorial subdivision of a larger country.
-
D.
territorialDesignation
Indicates that an entity is assigned, defined, or recognized in terms of a specific geographic or territorial area.
-
E.
betweenSubnationalUnits
Indicates a relationship that occurs or holds between two or more subnational administrative units (such as states, provinces, or regions) within a country.
- 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_69a88715dbbc8190b2299e29e955d997 |
completed | March 4, 2026, 7:25 p.m. |
| NER | Named-entity recognition | batch_69abb91055d88190a980e7b42e5895d4 |
completed | March 7, 2026, 5:35 a.m. |
| PD | Predicate disambiguation | batch_69abb79c97d48190b3147430ed39faa9 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:37 p.m.