Triple
T19983314
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Watts riots |
E493869
|
entity |
| Predicate | numberOfTroopsDeployed |
P6153
|
FINISHED |
| Object | over 14000 National Guard 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: over 14000 National Guard troops | Statement: [Watts riots, numberOfTroopsDeployed, over 14000 National Guard troops]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfTroopsDeployed Context triple: [Watts riots, numberOfTroopsDeployed, over 14000 National Guard troops]
-
A.
numberOfTroopsInvolved
chosen
Indicates the quantity of military personnel participating in or assigned to a specific operation, event, or engagement.
-
B.
suppliedTroopsTo
Indicates that one entity provided military personnel or forces to another entity.
-
C.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
D.
commandingForceSize
Indicates the size or magnitude of the military or organizational force that is exercising command or control in a given context.
-
E.
peakTroopDeployment
Indicates the maximum number of troops that were deployed at any single point during a specified conflict or operation.
- 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_69da626a67648190af9653832a3aeced |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e65d14c3c08190b1ba8f4da08a4ccf |
completed | April 20, 2026, 5:06 p.m. |
| PD | Predicate disambiguation | batch_69e537fae79c81909eae39500766d0b6 |
completed | April 19, 2026, 8:15 p.m. |
Created at: April 11, 2026, 3:28 p.m.