Triple
T3502537
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | FMNH PR 2081 |
E74000
|
entity |
| Predicate | numberOfBonesRecovered |
P48557
|
FINISHED |
| Object | over 250 |
—
|
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 250 | Statement: [FMNH PR 2081, numberOfBonesRecovered, over 250]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfBonesRecovered Context triple: [FMNH PR 2081, numberOfBonesRecovered, over 250]
-
A.
numberOfBurials
Indicates the total count of burial events associated with a given entity.
-
B.
skeletonCompleteness
Indicates the degree to which an entity’s skeleton is present, intact, or fully preserved in relation to its expected complete form.
-
C.
numberOfSuspectedVictims
Indicates the count of individuals believed or alleged to be victims in a particular incident, case, or context.
-
D.
numberOfColossalHeads
Indicates the quantity of colossal heads associated with or attributed to a given subject.
-
E.
recoveredIn
Indicates that something lost, damaged, or impaired has been restored or regained within a particular context, process, or location.
- 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_69ad85ce7a9c81909ddc5cf0cb67a6e3 |
completed | March 8, 2026, 2:21 p.m. |
| NER | Named-entity recognition | batch_69adbbef47988190b5b3fe2e452b9ac8 |
completed | March 8, 2026, 6:11 p.m. |
| PD | Predicate disambiguation | batch_69adae0cd8b0819099da300af09880da |
completed | March 8, 2026, 5:12 p.m. |
| PDg | Predicate description generation | batch_69adaef1037c819082c7af949ec85360 |
completed | March 8, 2026, 5:16 p.m. |
Created at: March 8, 2026, 3:18 p.m.