Triple
T7402054
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tabuk expedition |
E170771
|
entity |
| Predicate | armySizeApprox |
P6153
|
FINISHED |
| Object | around 30,000 men |
—
|
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: around 30,000 men | Statement: [Tabuk expedition, armySizeApprox, around 30,000 men]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: armySizeApprox Context triple: [Tabuk expedition, armySizeApprox, around 30,000 men]
-
A.
militarySize
Indicates the total number of personnel in a military force, typically including active-duty members and sometimes reserves.
-
B.
typeOfTroops
Indicates the specific category or kind of military forces involved in or associated with an entity or event.
-
C.
garrisonSize
Indicates the number of troops or defenders stationed at a particular location as its garrison.
-
D.
restrictedArmySizeOf
Indicates that one entity imposes a limitation or cap on the allowable size of another entity’s army.
-
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_69c68a5f04188190ac266569c9280347 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f26d6d6081909c7272a9ccae0d97 |
completed | March 27, 2026, 9:11 p.m. |
| PD | Predicate disambiguation | batch_69c6f0323b2c819098ab72c33e6d8534 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:10 p.m.