Triple
T4900900
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wood |
E109794
|
entity |
| Predicate | hasFrequencyRankInEngland |
P60551
|
FINISHED |
| Object | common |
—
|
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: common | Statement: [Wood, hasFrequencyRankInEngland, common]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFrequencyRankInEngland Context triple: [Wood, hasFrequencyRankInEngland, common]
-
A.
hasPopulationRankInUK
Indicates the relative position of an entity’s population size compared to other entities within the United Kingdom.
-
B.
selectionRankingFrequency
Indicates how often an entity is chosen or ranked in a particular position within a selection or ordering process.
-
C.
rankingInEnglandByHeight
Indicates the relative position of an entity in an ordered list based on its height specifically within the context of England.
-
D.
orderRankWithinOrderOfTheBritishEmpire
Indicates the specific hierarchical rank an individual holds within the Order of the British Empire honors system.
-
E.
frequencyRankInUnitedStates
Indicates the relative position of something in an ordered list based on how frequently it occurs within the United States.
- 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_69bd441180708190ba42ffb44fea533a |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd706245e48190a61d573438461c30 |
completed | March 20, 2026, 4:05 p.m. |
| PD | Predicate disambiguation | batch_69bd6c306b188190a08a7856beb76db4 |
completed | March 20, 2026, 3:48 p.m. |
| PDg | Predicate description generation | batch_69bd7060f9988190afdf98eb0a38515d |
completed | March 20, 2026, 4:05 p.m. |
Created at: March 20, 2026, 1:28 p.m.