Triple
T31746127
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Umballa |
E810274
|
entity |
| Predicate | hadMilitaryCantonment |
P100128
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Umballa, hadMilitaryCantonment, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hadMilitaryCantonment Context triple: [Umballa, hadMilitaryCantonment, true]
-
A.
establishedAsCantonmentBy
Indicates that an entity was designated or set up as a cantonment by a specified agent or authority.
-
B.
wasMilitaryHeadquartersOf
Indicates that a place or facility served as the main command center or headquarters for a specific military force or organization.
-
C.
hadMilitaryPost
Indicates that an entity held an official position or assignment within a military organization.
-
D.
hostsMilitaryInstallation
chosen
Indicates that a location contains or accommodates a military base, facility, or installation operated by armed forces.
-
E.
formerMilitaryBase
Indicates that a location was previously used as a military base but no longer serves that function.
- 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_69f348e233cc819083b6695f70cd75d8 |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6ab4db95c819083ff04ad3069881b |
completed | May 3, 2026, 1:56 a.m. |
| PD | Predicate disambiguation | batch_69f6aa20a1588190a53533fc9764efb2 |
completed | May 3, 2026, 1:51 a.m. |
Created at: April 30, 2026, 11:26 p.m.