Triple
T4346662
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Douaumont Ossuary |
E97919
|
entity |
| Predicate | numberOfUnidentifiedRemains |
P56191
|
FINISHED |
| Object | over 130000 |
—
|
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 130000 | Statement: [Douaumont Ossuary, numberOfUnidentifiedRemains, over 130000]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfUnidentifiedRemains Context triple: [Douaumont Ossuary, numberOfUnidentifiedRemains, over 130000]
-
A.
finalDispositionOfRemains
Indicates the relationship specifying how a person's physical remains are ultimately handled, treated, or placed after death.
-
B.
numberOfBonesRecovered
Indicates the count of bones that have been found and recovered in relation to a particular subject or event.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
numberOfMassGraves
Indicates the quantity of mass graves associated with or present at a given entity or location.
-
E.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
- 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_69b34548402c819085ab68b27c235a87 |
completed | March 12, 2026, 10:59 p.m. |
| NER | Named-entity recognition | batch_69b3518d6728819084a2f40ae0bd3ac8 |
completed | March 12, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69b34f4fe1c481908d6d66e15697c04b |
completed | March 12, 2026, 11:42 p.m. |
| PDg | Predicate description generation | batch_69b350d1649881908fa6556d875a8b4d |
completed | March 12, 2026, 11:48 p.m. |
Created at: March 12, 2026, 11:15 p.m.