Triple
T11659026
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Enderman |
E277076
|
entity |
| Predicate | takesDamageFrom |
P100770
|
FINISHED |
| Object | water contact |
—
|
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: water contact | Statement: [Enderman, takesDamageFrom, water contact]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: takesDamageFrom Context triple: [Enderman, takesDamageFrom, water contact]
-
A.
damageTo
Indicates a relationship where one entity causes harm, loss, or deterioration to another entity.
-
B.
tookHeavyDamageAt
Indicates that an entity experienced severe or substantial damage at a specific location or point in time.
-
C.
sufferedDamageTo
Indicates that one entity has experienced harm, loss, or deterioration affecting another entity or one of its parts.
-
D.
damagedBy
Indicates that one entity has caused harm, impairment, or deterioration to another entity.
-
E.
damageLeadsTo
Indicates that one instance of damage causally results in or contributes to another specified outcome or condition.
- 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_69d6aafbb3c081908a9cdb4ecb8d981d |
completed | April 8, 2026, 7:22 p.m. |
| NER | Named-entity recognition | batch_69d8a3d19c788190826d849a6ffedc72 |
completed | April 10, 2026, 7:16 a.m. |
| PD | Predicate disambiguation | batch_69d88a73f9ac819095662042804bf40a |
completed | April 10, 2026, 5:28 a.m. |
| PDg | Predicate description generation | batch_69d890458d948190b15054c9ba0fd923 |
completed | April 10, 2026, 5:53 a.m. |
Created at: April 8, 2026, 9:39 p.m.