Triple
T13192500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lohagarh Fort |
E314027
|
entity |
| Predicate | numberOfBritishAttacksResisted |
P108975
|
FINISHED |
| Object | multiple |
—
|
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: multiple | Statement: [Lohagarh Fort, numberOfBritishAttacksResisted, multiple]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBritishAttacksResisted Context triple: [Lohagarh Fort, numberOfBritishAttacksResisted, multiple]
-
A.
strengthBritishForces
Indicates the numerical size or combat capacity of British military forces in a given context or operation.
-
B.
navalOpposition
Indicates a relationship where one party actively resists, confronts, or acts against another using naval or maritime military forces.
-
C.
wasBesiegedBy
Indicates that an entity (typically a place or stronghold) was subjected to a military siege carried out by another entity.
-
D.
wasInvadedBy
Indicates that a place or territory was subjected to an incursion or attack carried out by another entity or group.
-
E.
countryAttacked
Indicates that one country has carried out an attack against another country.
- 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_69d806ae1e08819090d95bfe1538cc17 |
completed | April 9, 2026, 8:06 p.m. |
| NER | Named-entity recognition | batch_69d98cf054f88190b05ced98d5a22a62 |
completed | April 10, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69d98bc6bc108190b5a6a265bf6e9fd4 |
completed | April 10, 2026, 11:46 p.m. |
| PDg | Predicate description generation | batch_69d98ceeb22c8190a6be666031d9e5a4 |
completed | April 10, 2026, 11:51 p.m. |
Created at: April 9, 2026, 9:15 p.m.