Triple
T9175304
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tacoma Narrows |
E220183
|
entity |
| Predicate | hasUnderwaterFeature |
P23553
|
FINISHED |
| Object | deep central channel |
—
|
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: deep central channel | Statement: [Tacoma Narrows, hasUnderwaterFeature, deep central channel]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasUnderwaterFeature Context triple: [Tacoma Narrows, hasUnderwaterFeature, deep central channel]
-
A.
submergedFeatures
chosen
Indicates that certain features or elements are located beneath the surface of a body of water or otherwise covered by liquid.
-
B.
hasWaterFeatures
Indicates that an entity includes or is associated with water-related elements such as fountains, ponds, streams, or similar features.
-
C.
hasDivingComponent
Indicates that an activity, event, or process includes or involves a diving-related element or action.
-
D.
hasUnderwaterThemedRestaurant
Indicates that an entity operates or contains a restaurant whose design, ambiance, or concept is themed around underwater or oceanic elements.
-
E.
hasWaterCharacteristics
Indicates that one entity possesses qualities, properties, or behaviors characteristic of water.
- 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_69ca83e589948190ac9907819db11ddf |
completed | March 30, 2026, 2:08 p.m. |
| NER | Named-entity recognition | batch_69ccbfa2f9708190a955bf28a4f04004 |
completed | April 1, 2026, 6:48 a.m. |
| PD | Predicate disambiguation | batch_69cc660761d88190ab6134b43b376964 |
completed | April 1, 2026, 12:25 a.m. |
Created at: March 30, 2026, 7:23 p.m.