Triple
T35807030
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mankind |
E1035127
|
entity |
| Predicate | tookBumpFrom |
P184136
|
FINISHED |
| Object | top of Hell in a Cell through announce table |
—
|
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: top of Hell in a Cell through announce table | Statement: [Mankind, tookBumpFrom, top of Hell in a Cell through announce table]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tookBumpFrom Context triple: [Mankind, tookBumpFrom, top of Hell in a Cell through announce table]
-
A.
bodyTakenTo
Indicates that a deceased person's body is transported or moved to a particular location.
-
B.
takenInBy
Indicates that one entity is absorbed, ingested, or otherwise brought inside and contained by another entity.
-
C.
takenBy
Indicates that something is captured, acquired, or received by a particular entity.
-
D.
takenAs
Indicates that one entity is regarded, used, or accepted in the role, capacity, or form of another entity.
-
E.
cellsTakenFrom
Indicates that cells have been removed or extracted from a particular source 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_69f76e1762408190b885a8456862e372 |
completed | May 3, 2026, 3:47 p.m. |
| NER | Named-entity recognition | batch_69f7aaabb58c8190bf81673608ecfb6e |
completed | May 3, 2026, 8:06 p.m. |
| PD | Predicate disambiguation | batch_69f7a8d219f8819081dc4ce3c83ca0cb |
completed | May 3, 2026, 7:58 p.m. |
| PDg | Predicate description generation | batch_69f7aa6795f481908940838ee7041ff5 |
completed | May 3, 2026, 8:04 p.m. |
Created at: May 3, 2026, 4:06 p.m.