Triple
T30087543
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | lateral sulcus |
E764637
|
entity |
| Predicate | usedAsLandmarkIn |
P43158
|
FINISHED |
| Object | functional neuroimaging |
—
|
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: functional neuroimaging | Statement: [lateral sulcus, usedAsLandmarkIn, functional neuroimaging]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: usedAsLandmarkIn Context triple: [lateral sulcus, usedAsLandmarkIn, functional neuroimaging]
-
A.
eraOfUseAsLandmark
Indicates the historical time period during which something was used or recognized as a landmark.
-
B.
isLandmarkFor
chosen
Indicates that one entity serves as a notable or significant reference point or attraction for another entity, such as a place, route, or area.
-
C.
includesLandmark
Indicates that one location or area contains or encompasses a specific landmark within its boundaries.
-
D.
usedInMonument
Indicates that something serves as a material, component, or element incorporated into the construction or design of a monument.
-
E.
isLandmarkNameFor
Indicates that one entity is the name used to identify a particular landmark.
- 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_69f22473c0fc8190a926a8051b3b378b |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd02680d948190a3463fb119ba8556 |
completed | May 7, 2026, 9:21 p.m. |
| PD | Predicate disambiguation | batch_69fcf89c69b4819082bbc564bd15137d |
completed | May 7, 2026, 8:39 p.m. |
Created at: April 29, 2026, 7:04 p.m.