Triple
T9418679
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Anzick site |
E227092
|
entity |
| Predicate | hasHumanRemains |
P62966
|
FINISHED |
| Object | infant male individual |
—
|
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: infant male individual | Statement: [Anzick site, hasHumanRemains, infant male individual]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHumanRemains Context triple: [Anzick site, hasHumanRemains, infant male individual]
-
A.
hasBuriedRemains
Indicates that one entity contains or is the location of the buried remains of another entity.
-
B.
numberOfUnidentifiedRemains
Indicates the count of human remains that have not yet been identified in a given context or case.
-
C.
hasBurialsOf
chosen
Indicates that a location or site contains or includes the burial places of certain individuals or groups.
-
D.
hasMannerOfDeath
Indicates the specific way or circumstances in which an entity died, such as natural causes, accident, homicide, or suicide.
-
E.
hasTissue
Indicates that one entity possesses, contains, or is associated with a specific tissue of another entity.
- 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_69ca84359e7c819091148ba4b670e436 |
completed | March 30, 2026, 2:09 p.m. |
| NER | Named-entity recognition | batch_69cd68cd1e3481909abcb715e2398120 |
completed | April 1, 2026, 6:49 p.m. |
| PD | Predicate disambiguation | batch_69cca550777c819094e1851a6127cbbc |
completed | April 1, 2026, 4:55 a.m. |
Created at: March 30, 2026, 7:48 p.m.