Triple
T16395845
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Latin cross |
E398176
|
entity |
| Predicate | hasHorizontalBeamPosition |
P123257
|
FINISHED |
| Object | above midpoint of vertical beam |
—
|
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: above midpoint of vertical beam | Statement: [Latin cross, hasHorizontalBeamPosition, above midpoint of vertical beam]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHorizontalBeamPosition Context triple: [Latin cross, hasHorizontalBeamPosition, above midpoint of vertical beam]
-
A.
hasBeamlines
Indicates that one entity possesses, contains, or is associated with one or more beamlines.
-
B.
hasTypicalBeam
Indicates that an entity is associated with a characteristic or standard type of beam it commonly uses or possesses.
-
C.
hasBeamSpecies
Indicates a relationship where an object or structure possesses or is associated with a particular type or species of beam.
-
D.
hasIBeamColumns
Indicates that an entity includes or is supported by structural columns made from I-beams.
-
E.
hasHeadPosition
Indicates the specific spatial position or orientation of an entity’s head relative to a reference frame or context.
- 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_69d87f2950248190bc8ad9b9bebdc8c8 |
completed | April 10, 2026, 4:40 a.m. |
| NER | Named-entity recognition | batch_69e326462298819087091dc935f0f916 |
completed | April 18, 2026, 6:35 a.m. |
| PD | Predicate disambiguation | batch_69e226f94dd48190b7b8e0e983738a67 |
completed | April 17, 2026, 12:26 p.m. |
| PDg | Predicate description generation | batch_69e24555bb6c8190977cf5c5f9149056 |
completed | April 17, 2026, 2:36 p.m. |
Created at: April 10, 2026, 5:09 a.m.