Triple
T37105361
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | 6489 Golevka |
E918824
|
entity |
| Predicate | hasMeasuredEffect |
P76547
|
FINISHED |
| Object | Yarkovsky effect |
—
|
NE NERFINISHED |
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: Yarkovsky effect | Statement: [6489 Golevka, hasMeasuredEffect, Yarkovsky effect]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasMeasuredEffect Context triple: [6489 Golevka, hasMeasuredEffect, Yarkovsky effect]
-
A.
measuredEffect
chosen
Indicates that an action or process has produced a specific, quantified outcome or impact on something.
-
B.
hasMeasuredParameter
Indicates that an entity has a specific parameter that has been quantitatively measured or recorded.
-
C.
hasMeasurement
Indicates that an entity is associated with a specific measured value, often including a unit or measurement context.
-
D.
hasEffectIn
Indicates that one entity produces, causes, or exerts an effect within a specified context, system, or environment.
-
E.
hasIntendedEffect
Indicates that one entity is expected or designed to produce a particular effect or outcome on another entity or context.
- 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_69f76e9b99c8819096164b21ff5bd996 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ff7ae5d088819089aa3b6360b6b749 |
completed | May 9, 2026, 6:20 p.m. |
| PD | Predicate disambiguation | batch_69ff7a4df6488190bf60d675b36b1d6d |
completed | May 9, 2026, 6:17 p.m. |
Created at: May 3, 2026, 4:14 p.m.