Triple
T7338060
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Diehard |
E169179
|
entity |
| Predicate | usesGridStates |
P29137
|
FINISHED |
| Object | alive and dead cells |
—
|
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: alive and dead cells | Statement: [Diehard, usesGridStates, alive and dead cells]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usesGridStates Context triple: [Diehard, usesGridStates, alive and dead cells]
-
A.
usedInState
Indicates that something is employed, applied, or functions within a particular state or condition.
-
B.
cellStates
chosen
Indicates the various conditions or phases that a cell can be in at a given time.
-
C.
hasObserverStates
Indicates that an entity is associated with one or more observer-specific states or conditions under which it is perceived or evaluated.
-
D.
historicalState
Indicates that an entity existed in a particular state or condition during a specified time in the past.
-
E.
aggregateState
Indicates the overall or combined condition or status resulting from multiple underlying states or components.
- 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_69c68a57710481909f0c1f3c6ebdb6f2 |
completed | March 27, 2026, 1:47 p.m. |
| NER | Named-entity recognition | batch_69c6f347f25081908e6086d4073295f5 |
completed | March 27, 2026, 9:14 p.m. |
| PD | Predicate disambiguation | batch_69c6f028fd748190b2ea5c3081958a42 |
completed | March 27, 2026, 9:01 p.m. |
Created at: March 27, 2026, 3:04 p.m.