Triple
T10876793
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Cristóvão da Gama |
E256818
|
entity |
| Predicate | numberOfTroopsCommanded |
P6153
|
FINISHED |
| Object | approximately 400 Portuguese musketeers |
—
|
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: approximately 400 Portuguese musketeers | Statement: [Cristóvão da Gama, numberOfTroopsCommanded, approximately 400 Portuguese musketeers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTroopsCommanded Context triple: [Cristóvão da Gama, numberOfTroopsCommanded, approximately 400 Portuguese musketeers]
-
A.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
B.
commandingForce2Strength
Indicates that a commanding force possesses or exerts a particular level or measure of strength.
-
C.
commandedForcesOf
Indicates that one entity held command authority over the military or armed forces associated with another entity.
-
D.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
E.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
- 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_69d6aa848804819081b2713ca0bedf06 |
completed | April 8, 2026, 7:20 p.m. |
| NER | Named-entity recognition | batch_69d751ad8cdc819093eafaf12fc23b15 |
completed | April 9, 2026, 7:13 a.m. |
| PD | Predicate disambiguation | batch_69d70d360c388190a3d829fe8862434f |
completed | April 9, 2026, 2:21 a.m. |
Created at: April 8, 2026, 9:21 p.m.