Triple
T627842
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Battle of Bladensburg |
E15857
|
entity |
| Predicate | approximateStrengthBritish |
P2981
|
FINISHED |
| Object | about 4,000 troops |
—
|
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: about 4,000 troops | Statement: [Battle of Bladensburg, approximateStrengthBritish, about 4,000 troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: approximateStrengthBritish Context triple: [Battle of Bladensburg, approximateStrengthBritish, about 4,000 troops]
-
A.
estimatedStrength
chosen
Indicates that a value represents an approximate or inferred level, magnitude, or intensity of something rather than a precisely measured strength.
-
B.
hasBritishAccent
Indicates that the subject speaks with a British accent.
-
C.
strengthensFrom
Indicates that one entity becomes stronger, more effective, or more intense as a result of influence, support, or input from another entity.
-
D.
troopStrengthAlliedApprox
Indicates that the approximate troop strength of one entity is being assessed or reported in relation to its allied forces.
-
E.
strengthDescription
Indicates a description or characterization of the degree of strength associated with an entity or relationship.
- 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_69a4935c131c8190a5378c6bf101e8cc |
completed | March 1, 2026, 7:28 p.m. |
| NER | Named-entity recognition | batch_69a49e59e2688190b3c18b17c5db1e2b |
completed | March 1, 2026, 8:15 p.m. |
| PD | Predicate disambiguation | batch_69a49d01b29081908be87e4cd7726ff1 |
completed | March 1, 2026, 8:09 p.m. |
Created at: March 1, 2026, 7:35 p.m.