Triple
T5389847
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kitayama sugi |
E120293
|
entity |
| Predicate | woodQuality |
P1357
|
FINISHED |
| Object | high-quality |
—
|
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: high-quality | Statement: [Kitayama sugi, woodQuality, high-quality]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: woodQuality Context triple: [Kitayama sugi, woodQuality, high-quality]
-
A.
woodProperty
chosen
Indicates that one entity specifies or characterizes a property or attribute of wood associated with another entity.
-
B.
materialUsed
Indicates that one entity is made from, incorporates, or utilizes the other entity as its material or substance.
-
C.
isConifer
Indicates that the subject is a coniferous plant, typically bearing cones and having needle-like or scale-like evergreen leaves.
-
D.
hasGrainQuality
Indicates that an entity possesses a particular level or type of grain quality, characterizing the quality attributes of its grain.
-
E.
isWoodyPlant
Indicates that the subject is a plant characterized by persistent, woody stems or trunks that remain above ground year-round.
- 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_69bd46354c648190a38b26f107010a96 |
completed | March 20, 2026, 1:05 p.m. |
| NER | Named-entity recognition | batch_69bd8716ae9c8190a729222a8b9eb460 |
completed | March 20, 2026, 5:42 p.m. |
| PD | Predicate disambiguation | batch_69bd8463a9c88190bd760378f3026180 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2:04 p.m.