Triple
T4589641
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Hangzhou Bay |
E103450
|
entity |
| Predicate | hasAverageWidth |
P19786
|
FINISHED |
| Object | approximately 100 kilometers |
—
|
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: approximately 100 kilometers | Statement: [Hangzhou Bay, hasAverageWidth, approximately 100 kilometers]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasAverageWidth Context triple: [Hangzhou Bay, hasAverageWidth, approximately 100 kilometers]
-
A.
hasWidth
Indicates that an entity possesses a specific measurement or extent along its width dimension.
-
B.
typicalWidth
chosen
Indicates the usual or characteristic width associated with an entity, as opposed to an exact or measured width in a specific instance.
-
C.
hasApproximateMaximumWidth
Indicates that an entity’s maximum width is known only approximately, rather than as an exact value.
-
D.
hasAverageDepth
Indicates that an entity possesses a specified mean depth value, typically measured over its entire extent or area.
-
E.
typicalHeight
Indicates the usual or characteristic height associated with an entity, such as a person, object, or species.
- 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_69bd43dccaf08190aa89e9991a289719 |
completed | March 20, 2026, 12:55 p.m. |
| NER | Named-entity recognition | batch_69bd592232888190af33c47636ca835d |
completed | March 20, 2026, 2:26 p.m. |
| PD | Predicate disambiguation | batch_69bd522acbcc8190bf24d9517793a2c1 |
completed | March 20, 2026, 1:56 p.m. |
Created at: March 20, 2026, 1:11 p.m.