Triple
T31535234
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | locus coeruleus |
E804585
|
entity |
| Predicate | bilaterallyPaired |
P171934
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [locus coeruleus, bilaterallyPaired, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: bilaterallyPaired Context triple: [locus coeruleus, bilaterallyPaired, true]
-
A.
isBilateral
Indicates that the relationship or interaction involves two sides, parties, or entities mutually.
-
B.
typicalBilateralEquivalent
Indicates that two entities are considered standard or typical counterparts to each other in a bilateral relationship or comparison.
-
C.
dualPair
Indicates that two entities form a dual pair, standing in a mathematically defined dual relationship where each is the dual counterpart of the other.
-
D.
bilateralRelation
Indicates a mutual or two-way relationship between two entities, where each affects or interacts with the other.
-
E.
pairedInDoubleBillWith
Indicates that two performances, films, or shows are scheduled or presented together as a combined double-feature program.
- 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_69f348d03ef88190a2b73d7b94b9e02d |
completed | April 30, 2026, 12:19 p.m. |
| NER | Named-entity recognition | batch_69f6a956e9b08190bf83547bba8e8147 |
completed | May 3, 2026, 1:48 a.m. |
| PD | Predicate disambiguation | batch_69f6a75656e081908739ed9e2f600e42 |
completed | May 3, 2026, 1:39 a.m. |
| PDg | Predicate description generation | batch_69f6a8036ab481908019f2f071fa406e |
completed | May 3, 2026, 1:42 a.m. |
Created at: April 30, 2026, 10:03 p.m.