Triple
T12106005
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Afghan War Diary leak |
E288305
|
entity |
| Predicate | numberOfDocuments |
P59623
|
FINISHED |
| Object | over 75,000 |
—
|
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 75,000 | Statement: [Afghan War Diary leak, numberOfDocuments, over 75,000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfDocuments Context triple: [Afghan War Diary leak, numberOfDocuments, over 75,000]
-
A.
documentNumber
Indicates the unique identifying number assigned to a specific document in the relationship.
-
B.
documentsNow
Indicates that an entity is currently documenting, recording, or writing about another entity at the present time.
-
C.
numberOfCounts
Indicates the total quantity or tally of discrete occurrences, items, or instances associated with an entity or event.
-
D.
numberOfTexts
Indicates the quantity or count of text messages associated with a given entity or interaction.
-
E.
numberOfEntries
chosen
Indicates the total count of individual items, records, or instances associated with a given entity or context.
- 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_69d6ab4a5c448190a110d1273314b21a |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d9164ada5081908676bd9e5947268a |
completed | April 10, 2026, 3:24 p.m. |
| PD | Predicate disambiguation | batch_69d9150497408190921334d21503375a |
completed | April 10, 2026, 3:19 p.m. |
Created at: April 8, 2026, 9:49 p.m.