Triple
T3274202
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Fendouzhe |
E68719
|
entity |
| Predicate | hasCrewCompartmentMaterial |
P47038
|
FINISHED |
| Object | titanium alloy |
—
|
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: titanium alloy | Statement: [Fendouzhe, hasCrewCompartmentMaterial, titanium alloy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasCrewCompartmentMaterial Context triple: [Fendouzhe, hasCrewCompartmentMaterial, titanium alloy]
-
A.
hasCrewCapacity
Indicates that an entity is capable of accommodating a specified number of crew members.
-
B.
chassisMaterialFeature
Indicates that an entity has a chassis characterized by a specific material-related feature or property.
-
C.
intendedCrewVehicle
Indicates that a particular vehicle is designated or planned to be used by a specific crew.
-
D.
carbodyMaterial
Indicates the material from which a vehicle’s body or main structural shell is made.
-
E.
hasCargoDoorVariant
Indicates that one entity is a specific cargo-door-equipped version or configuration variant of another entity.
- F. None of above. chosen
Provenance (4 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_69ad859b54f881909bf530d549caf2fd |
completed | March 8, 2026, 2:20 p.m. |
| NER | Named-entity recognition | batch_69adaff8a440819092509bc8511b2785 |
completed | March 8, 2026, 5:20 p.m. |
| PD | Predicate disambiguation | batch_69ada420167c81909b6e2702db296d9e |
completed | March 8, 2026, 4:30 p.m. |
| PDg | Predicate description generation | batch_69ada525bb2c8190b773efe6d696b6ab |
completed | March 8, 2026, 4:34 p.m. |
Created at: March 8, 2026, 3:10 p.m.