Triple
T20079806
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | UTDC ALRV |
E499966
|
entity |
| Predicate | articulationCount |
P138637
|
FINISHED |
| Object | 2 |
—
|
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: 2 | Statement: [UTDC ALRV, articulationCount, 2]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: articulationCount Context triple: [UTDC ALRV, articulationCount, 2]
-
A.
hasArticulation
Indicates that one entity possesses or exhibits a specific type or structure of articulation in relation to another entity or system.
-
B.
phonemeInventorySize
Indicates the number of distinct phonemes present in a language’s sound system.
-
C.
usesArticulators
Indicates that an entity performs an action or produces a signal by employing specific speech or movement articulators (e.g., tongue, lips, jaw).
-
D.
hasArticulationType
Indicates the specific manner or type of connection or joint by which two parts or entities are linked or articulated.
-
E.
numberOfSyllabicSignsApprox
Indicates an approximate count of syllabic signs associated with an 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_69da627770948190997f486f9a2e370f |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e6643f93208190ae2a413f88ea9aed |
completed | April 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69e54cf369b88190931532420517dac7 |
completed | April 19, 2026, 9:45 p.m. |
| PDg | Predicate description generation | batch_69e54fc20888819083c9118a09d0d2dc |
completed | April 19, 2026, 9:57 p.m. |
Created at: April 11, 2026, 3:40 p.m.