Triple
T26966582
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Post correspondence problem |
E679187
|
entity |
| Predicate | dominoCountCondition |
P169245
|
FINISHED |
| Object | undecidable for sufficiently many dominoes |
—
|
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: undecidable for sufficiently many dominoes | Statement: [Post correspondence problem, dominoCountCondition, undecidable for sufficiently many dominoes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: dominoCountCondition Context triple: [Post correspondence problem, dominoCountCondition, undecidable for sufficiently many dominoes]
-
A.
roleInDomino
Indicates that an entity participates in a domino effect or chain of events by occupying a specific role or position within that causal sequence.
-
B.
numberOfDomes
Indicates the quantity of domes that an entity possesses or is associated with.
-
C.
hasLeadCountPerSide
Indicates the number of lead elements or units associated with each side in a given context or configuration.
-
D.
tileCount
Indicates the number of tiles associated with or contained by a given entity or area.
-
E.
numberOfChips
Indicates the quantity of chips associated with a given entity or situation.
- 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_69eeeb4f3a448190b1e94b2d4776c16e |
completed | April 27, 2026, 4:51 a.m. |
| NER | Named-entity recognition | batch_69f67d691a948190afa7fb19ae7d4ac5 |
completed | May 2, 2026, 10:40 p.m. |
| PD | Predicate disambiguation | batch_69f678cc272081909e5c70f1bc7407f0 |
completed | May 2, 2026, 10:21 p.m. |
| PDg | Predicate description generation | batch_69f67c9ec1708190b26ccf402ed7b106 |
completed | May 2, 2026, 10:37 p.m. |
Created at: April 27, 2026, 6:36 a.m.