Triple
T33027395
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | CDUP |
E845077
|
entity |
| Predicate | effectOnPath |
P190074
|
FINISHED |
| Object | moves one level up in directory hierarchy |
—
|
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: moves one level up in directory hierarchy | Statement: [CDUP, effectOnPath, moves one level up in directory hierarchy]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: effectOnPath Context triple: [CDUP, effectOnPath, moves one level up in directory hierarchy]
-
A.
effectOnOutput
Indicates how one factor, action, or condition influences or changes the resulting output of a process or system.
-
B.
effectOnWorld
Indicates how an entity’s actions or existence change, influence, or impact the state of the world.
-
C.
effectOnLens
Indicates the influence or impact that one entity has on the properties, behavior, or performance of a lens.
-
D.
effectOnUsage
Indicates how one factor or condition changes the way something is used, including the extent, manner, or frequency of its usage.
-
E.
capturesEffectOf
Indicates that one entity represents or records the impact, consequence, or outcome produced by another entity or process.
- 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_69f34950749c8190ae05cd27adb16d58 |
completed | April 30, 2026, 12:21 p.m. |
| NER | Named-entity recognition | batch_69fcab6e888881908ca9e18660928a40 |
completed | May 7, 2026, 3:10 p.m. |
| PD | Predicate disambiguation | batch_69fc4562a5b88190bad48f083a6dcdfa |
completed | May 7, 2026, 7:55 a.m. |
| PDg | Predicate description generation | batch_69fcab6d41a88190a3576b4b088dcabd |
completed | May 7, 2026, 3:10 p.m. |
Created at: May 1, 2026, 1:23 a.m.