Triple
T11996905
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | spinning top totem |
E285554
|
entity |
| Predicate | behaviorInReality |
P23475
|
FINISHED |
| Object | eventually topples |
—
|
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: eventually topples | Statement: [spinning top totem, behaviorInReality, eventually topples]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: behaviorInReality Context triple: [spinning top totem, behaviorInReality, eventually topples]
-
A.
behaviorNear
Indicates that one entity exhibits a behavior or action in close spatial proximity to another entity.
-
B.
behaviorObserved
chosen
Indicates that a particular behavior or action has been witnessed, recorded, or detected in relation to an entity or context.
-
C.
behaviorCode
Indicates the specific rule, standard, or classification code that governs or characterizes an entity’s behavior in a given context.
-
D.
femaleBehavior
Indicates that the behavior or actions being referred to are characteristic of, or typically associated with, females in the given context.
-
E.
realityStatus
Indicates the relationship between an entity and its state of existence or authenticity within a given context or world (e.g., real, fictional, hypothetical, simulated).
- 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_69d6ab44a77c8190a652f4b27164e4ef |
completed | April 8, 2026, 7:23 p.m. |
| NER | Named-entity recognition | batch_69d903c172788190b92042e9d10a48bf |
completed | April 10, 2026, 2:05 p.m. |
| PD | Predicate disambiguation | batch_69d902b245cc8190af96a9c2bd9c6250 |
completed | April 10, 2026, 2:01 p.m. |
Created at: April 8, 2026, 9:46 p.m.