Triple
T5338580
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lake Copais |
E123885
|
entity |
| Predicate | characteristicInAntiquity |
P18777
|
FINISHED |
| Object | prone to flooding |
—
|
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: prone to flooding | Statement: [Lake Copais, characteristicInAntiquity, prone to flooding]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: characteristicInAntiquity Context triple: [Lake Copais, characteristicInAntiquity, prone to flooding]
-
A.
reputationInAntiquity
Indicates the reputation or standing an entity had during ancient times.
-
B.
historicalCharacteristic
chosen
Indicates that an entity possesses a trait, feature, or quality that is rooted in or defined by its history or past events.
-
C.
traditionCharacteristic
Indicates that a particular quality, feature, or attribute is characteristic of, or typically associated with, a given tradition.
-
D.
countryDuringAntiquity
Indicates that an entity functioned as a country or political territory specifically during the historical period of antiquity.
-
E.
ancientCity
Indicates that the subject is a historically old or long-established city, typically originating from ancient times.
- 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_69bd464b07f8819095aa76577c9829e4 |
completed | March 20, 2026, 1:06 p.m. |
| NER | Named-entity recognition | batch_69bd85e86edc81908d87933db6489f91 |
completed | March 20, 2026, 5:37 p.m. |
| PD | Predicate disambiguation | batch_69bd845a62b081909782863865b257a9 |
completed | March 20, 2026, 5:31 p.m. |
Created at: March 20, 2026, 2 p.m.