Triple
T36703328
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Zoogoneticus tequila |
E906288
|
entity |
| Predicate | hasLateralLine |
P36502
|
FINISHED |
| Object | yes |
—
|
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: yes | Statement: [Zoogoneticus tequila, hasLateralLine, yes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLateralLine Context triple: [Zoogoneticus tequila, hasLateralLine, yes]
-
A.
hasLateralStructure
chosen
Indicates that one entity possesses or exhibits a structural feature oriented to or located on its side(s).
-
B.
hasStraightLines
Indicates that the related entity possesses or is characterized by straight, non-curved lines.
-
C.
hasLRTLine
Indicates that a location, station, or area is served by or lies along a specific light rail transit (LRT) line.
-
D.
hasDominantLines
Indicates that one element in a pair exhibits stronger, more prominent, or controlling linear features relative to the other.
-
E.
hasLateralityPattern
Indicates that something possesses a specific sidedness or lateral arrangement (e.g., left, right, bilateral) as a characteristic pattern.
- 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_69f76e7195c48190b5580c9cfb01e95f |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffb82be8148190a1c870d467a28c80 |
completed | May 9, 2026, 10:41 p.m. |
| PD | Predicate disambiguation | batch_69ffb7bbd550819094052e9a0d0ae320 |
completed | May 9, 2026, 10:39 p.m. |
Created at: May 3, 2026, 4:12 p.m.