Triple
T15477270
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Guilaki |
E376812
|
entity |
| Predicate | hasVerbFinalTendency |
P118400
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Guilaki, hasVerbFinalTendency, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasVerbFinalTendency Context triple: [Guilaki, hasVerbFinalTendency, true]
-
A.
hasInfinitiveVerbEnding
Indicates that a verb takes the infinitive form with a specific infinitive verb ending (such as “-to” in English or “-en” in German).
-
B.
hasVerbAspect
Indicates that a verb or verbal expression is associated with a particular grammatical aspect (such as perfective, imperfective, or progressive) describing the temporal structure of the action or state.
-
C.
hasPastTenseEnding
Indicates that a verb form ends with a morphological marker typically used to express past tense.
-
D.
hasAdverbEnding
Indicates that something (typically a word) ends with a suffix or form characteristic of an adverb.
-
E.
hasFutureTenseEnding
Indicates that a verb or expression carries a morphological ending marking future tense.
- 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_69d85cd21dcc81908646251b1c26ea00 |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e03f88a5dc8190a2d7830748e29180 |
completed | April 16, 2026, 1:46 a.m. |
| PD | Predicate disambiguation | batch_69ded2874b788190999158e0f043be21 |
completed | April 14, 2026, 11:49 p.m. |
| PDg | Predicate description generation | batch_69ded5deee00819099fa3e43313312e1 |
completed | April 15, 2026, 12:03 a.m. |
Created at: April 10, 2026, 3:34 a.m.