Triple
T33994823
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zihuatanejo port |
E871644
|
entity |
| Predicate | typicalVesselTypes |
P109622
|
FINISHED |
| Object | small fishing boats |
—
|
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: small fishing boats | Statement: [Zihuatanejo port, typicalVesselTypes, small fishing boats]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: typicalVesselTypes Context triple: [Zihuatanejo port, typicalVesselTypes, small fishing boats]
-
A.
typicalShipTypes
chosen
Indicates that the subject is commonly or characteristically associated with the specified types or categories of ships.
-
B.
vesselTypeServedOn
Indicates the type of vessel on which an entity has served or performed duty.
-
C.
hasVesselType
Indicates that an entity is associated with or classified by a specific type of vessel (e.g., ship, boat, or container).
-
D.
sponsoredVesselType
Indicates that one entity has provided sponsorship or financial backing specifically for a vessel of a given type.
-
E.
typicalVesselMaterial
Indicates the material that is most commonly or characteristically used to make a given vessel.
- 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_69f3499f8cbc81908de6ec89fa91ea8f |
completed | April 30, 2026, 12:22 p.m. |
| NER | Named-entity recognition | batch_6a037c8ae0248190b7e2ce4bf852c22d |
completed | May 12, 2026, 7:16 p.m. |
| PD | Predicate disambiguation | batch_6a0379f963908190846d232f386fd98f |
completed | May 12, 2026, 7:05 p.m. |
Created at: May 1, 2026, 1:50 a.m.