Triple
T36874066
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | El Agrio crater |
E911296
|
entity |
| Predicate | hasLakeColor |
P13022
|
FINISHED |
| Object | greenish |
—
|
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: greenish | Statement: [El Agrio crater, hasLakeColor, greenish]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasLakeColor Context triple: [El Agrio crater, hasLakeColor, greenish]
-
A.
hasWaterColor
chosen
Indicates that an entity possesses or is characterized by a particular color of water.
-
B.
hasLakeLandscape
Indicates that an entity features or is characterized by a landscape that includes a lake.
-
C.
hasDistinctWaterColorFor
Indicates that one entity exhibits a water color that is noticeably different or unique compared to another specified entity or context.
-
D.
hasLakeThatRepresents
Indicates a relationship where a lake serves as a symbolic or representative feature for something, such as a place, concept, or entity.
-
E.
waterColor
Indicates that one entity is the color or hue characteristic of water associated with another entity.
- 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_69f76e82339881909607a65c0503d941 |
completed | May 3, 2026, 3:49 p.m. |
| NER | Named-entity recognition | batch_69ffc1550cb481908628e446d9b67f7b |
completed | May 9, 2026, 11:20 p.m. |
| PD | Predicate disambiguation | batch_69ffc10a74708190ae90e2c378791f70 |
completed | May 9, 2026, 11:19 p.m. |
Created at: May 3, 2026, 4:13 p.m.