Triple
T129992
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Bay of Pigs Invasion |
E2632
|
entity |
| Predicate | numberOfInvaders |
P5177
|
FINISHED |
| Object | approximately 1400 |
—
|
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 1400 | Statement: [Bay of Pigs Invasion, numberOfInvaders, approximately 1400]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfInvaders Context triple: [Bay of Pigs Invasion, numberOfInvaders, approximately 1400]
-
A.
numberOfColonies
Indicates the count of distinct colonies associated with or possessed by a given entity.
-
B.
numberOfDomes
Indicates the quantity of domes that an entity possesses or is associated with.
-
C.
combatantStrength
Indicates the relative level of power, capability, or effectiveness one combatant has in a conflict or confrontation compared to others.
-
D.
fleetSize
Indicates the total number of vehicles, vessels, or units that collectively make up a fleet associated with an entity.
-
E.
numberBuilt
Indicates the total count of items or structures that have been constructed or produced.
- 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_69a2520c0f3481908b0ed054a2fca8d0 |
completed | Feb. 28, 2026, 2:25 a.m. |
| NER | Named-entity recognition | batch_69a257845c548190bfb49409988d1c57 |
completed | Feb. 28, 2026, 2:48 a.m. |
| PD | Predicate disambiguation | batch_69a2564da96c8190aa8204de25229c15 |
completed | Feb. 28, 2026, 2:43 a.m. |
| PDg | Predicate description generation | batch_69a256c72f6c81909b619b90d829d86e |
completed | Feb. 28, 2026, 2:45 a.m. |
Created at: Feb. 28, 2026, 2:30 a.m.