Triple
T16613257
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Nylanderia |
E403628
|
entity |
| Predicate | antennaSegments |
P123548
|
FINISHED |
| Object | 12-segmented antennae |
—
|
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: 12-segmented antennae | Statement: [Nylanderia, antennaSegments, 12-segmented antennae]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: antennaSegments Context triple: [Nylanderia, antennaSegments, 12-segmented antennae]
-
A.
numberOfAntennas
Indicates the quantity of antennas that an entity possesses or is associated with.
-
B.
antennaType
Indicates the specific kind or category of antenna associated with an entity or connection.
-
C.
notableAntenna
Indicates that an entity possesses an antenna that is particularly significant, prominent, or noteworthy in some relevant context.
-
D.
antennaRotation
Indicates the rotational movement or orientation change of an antenna relative to a reference frame or axis.
-
E.
numberOfAntennasInitial
Indicates the initial count of antennas associated with an entity before any changes or updates occur.
- 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_69d883880d0c81908b5fcd454e767b60 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e3609776d48190b6b8c7826ac575c4 |
completed | April 18, 2026, 10:44 a.m. |
| PD | Predicate disambiguation | batch_69e296aabc508190b3836a91b49113ad |
completed | April 17, 2026, 8:23 p.m. |
| PDg | Predicate description generation | batch_69e2d7fb02f481908885a226c2191231 |
completed | April 18, 2026, 1:01 a.m. |
Created at: April 10, 2026, 5:17 a.m.