Triple
T5927341
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Oise-Aisne American Cemetery |
E131845
|
entity |
| Predicate | numberOfNamesOnWallOfMissing |
P66755
|
FINISHED |
| Object | 241 |
—
|
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: 241 | Statement: [Oise-Aisne American Cemetery, numberOfNamesOnWallOfMissing, 241]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfNamesOnWallOfMissing Context triple: [Oise-Aisne American Cemetery, numberOfNamesOnWallOfMissing, 241]
-
A.
numberOfWorldWarIINamesOnWallOfMissing
Indicates the count of individuals from World War II whose names are inscribed on a commemorative Wall of the Missing.
-
B.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
C.
numberOfPeoplePressedToDeath
Indicates the number of people who were killed specifically by being pressed to death.
-
D.
numberOfMassGraves
Indicates the quantity of mass graves associated with or present at a given entity or location.
-
E.
numberOfVictimsKilled
Indicates the count of victims who were killed as a result of the referenced event or action.
- 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_69c0085b75e88190a632f9691f9da48b |
completed | March 22, 2026, 3:18 p.m. |
| NER | Named-entity recognition | batch_69c03c9239e08190bff7ef2bd6d21ae0 |
completed | March 22, 2026, 7:01 p.m. |
| PD | Predicate disambiguation | batch_69c033541d108190a34d1fde2fe9dacb |
completed | March 22, 2026, 6:22 p.m. |
| PDg | Predicate description generation | batch_69c03c8d579081909d7b97fc9014b5d7 |
completed | March 22, 2026, 7:01 p.m. |
Created at: March 22, 2026, 4 p.m.