Triple
T8764150
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | The Definition (interlude) |
E208286
|
entity |
| Predicate | hasRelativeLength |
P50260
|
FINISHED |
| Object | brief |
—
|
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: brief | Statement: [The Definition (interlude), hasRelativeLength, brief]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasRelativeLength Context triple: [The Definition (interlude), hasRelativeLength, brief]
-
A.
hasRelativeSize
Indicates that one entity’s size is being compared to another entity’s size, expressing a relative rather than absolute magnitude.
-
B.
relativeLength
chosen
Indicates a comparative relationship between entities based on how long they are relative to one another.
-
C.
hasRelativeLocation
Indicates that one entity is positioned in space in relation to another entity’s location.
-
D.
hasBaselineLength
Indicates that one entity has a specified baseline length measurement in relation to another entity or reference.
-
E.
isRelatively
Indicates that one entity is being described, measured, or evaluated in relation to another entity or reference point, rather than in absolute terms.
- 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_69ca835df7e08190ac875664cca8f9ca |
completed | March 30, 2026, 2:06 p.m. |
| NER | Named-entity recognition | batch_69cc5dfdef9881908a7f079d87e8e338 |
completed | March 31, 2026, 11:51 p.m. |
| PD | Predicate disambiguation | batch_69cc5c1884bc8190a46e8308db31f7ab |
completed | March 31, 2026, 11:43 p.m. |
Created at: March 30, 2026, 6:40 p.m.