Triple
T27952610
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Beam Drop (1984) |
E703468
|
entity |
| Predicate | numberOfSteelBeams |
P199287
|
FINISHED |
| Object | approximately 60 |
—
|
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: approximately 60 | Statement: [Beam Drop (1984), numberOfSteelBeams, approximately 60]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: numberOfSteelBeams Context triple: [Beam Drop (1984), numberOfSteelBeams, approximately 60]
-
A.
hasSteelStructure
Indicates that one entity incorporates or is built with a structural framework made of steel in relation to another entity.
-
B.
numberOfIronPieces
Indicates the quantity or count of iron pieces associated with an entity.
-
C.
hasVerticalBeamLength
Indicates that an entity is associated with a vertical beam whose length is specified.
-
D.
numberOfRivets
Indicates the quantitative relationship specifying how many rivets are associated with a given object or structure.
-
E.
typicalValueForSteel
Indicates that a given value represents a standard or commonly expected value associated with steel under typical conditions.
- 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_69ef840c8b2c8190946ae9522774ba51 |
completed | April 27, 2026, 3:43 p.m. |
| NER | Named-entity recognition | batch_69ff2d22ffb48190ae58ddf3c7e02869 |
completed | May 9, 2026, 12:48 p.m. |
| PD | Predicate disambiguation | batch_69ff2ac2e1c4819096cc64e94aef2ff0 |
completed | May 9, 2026, 12:38 p.m. |
| PDg | Predicate description generation | batch_69ff2d21f0a48190ad2ef5901cb07d93 |
completed | May 9, 2026, 12:48 p.m. |
Created at: April 27, 2026, 7:25 p.m.