Triple
T172735
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Durham boat |
E3510
|
entity |
| Predicate | hasTypicalLength |
P266
|
FINISHED |
| Object | about 18 meters |
—
|
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: about 18 meters | Statement: [Durham boat, hasTypicalLength, about 18 meters]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasTypicalLength Context triple: [Durham boat, hasTypicalLength, about 18 meters]
-
A.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
-
B.
hasStandardLetterCount
Indicates that an entity’s associated text or label contains a number of letters that matches a predefined standard or expected count.
-
C.
length
chosen
Indicates a measurement relationship where a value specifies how long something is from one end to the other.
-
D.
hasMainSpanLength
Indicates the relationship specifying the primary or main span’s length associated with an entity.
-
E.
typicalUnitSize
Indicates the standard or most common size or quantity in which something is typically measured, packaged, or used.
- 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_69a25374990081909766d30c79a18e0e |
completed | Feb. 28, 2026, 2:31 a.m. |
| NER | Named-entity recognition | batch_69a258e0b11c8190b7b5cf3c354c47ce |
completed | Feb. 28, 2026, 2:54 a.m. |
| PD | Predicate disambiguation | batch_69a256689f908190afeb5ee82022a911 |
completed | Feb. 28, 2026, 2:43 a.m. |
Created at: Feb. 28, 2026, 2:39 a.m.