Triple
T21479991
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | warship Michael |
E529961
|
entity |
| Predicate | numberOfGunsEstimate |
P43153
|
FINISHED |
| Object | over 100 guns |
—
|
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: over 100 guns | Statement: [warship Michael, numberOfGunsEstimate, over 100 guns]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfGunsEstimate Context triple: [warship Michael, numberOfGunsEstimate, over 100 guns]
-
A.
numberOfGuns
chosen
Indicates the quantity of guns associated with a given entity or situation.
-
B.
numberOfGunmen
Indicates the quantity of individuals identified as gunmen involved in a particular event or situation.
-
C.
armamentCount
Indicates the number of weapons or armaments associated with an entity.
-
D.
armamentCapacity
Indicates the maximum quantity or type of weapons or munitions that something is designed or allowed to carry.
-
E.
typeOfWeaponsStockpile
Indicates that one entity specifies the kind or category of weapons contained within another entity’s stockpile.
- 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_69e0c45acc3881908e38d3f28964152b |
completed | April 16, 2026, 11:13 a.m. |
| NER | Named-entity recognition | batch_69e9ea1b0130819088b8e96ddbb29317 |
completed | April 23, 2026, 9:44 a.m. |
| PD | Predicate disambiguation | batch_69e631ec1d048190b6da97da8222e413 |
completed | April 20, 2026, 2:02 p.m. |
Created at: April 16, 2026, 6:20 p.m.