Triple
T25839097
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Ötzi the Iceman |
E650884
|
entity |
| Predicate | tattooDistribution |
P159530
|
FINISHED |
| Object | back |
—
|
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: back | Statement: [Ötzi the Iceman, tattooDistribution, back]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: tattooDistribution Context triple: [Ötzi the Iceman, tattooDistribution, back]
-
A.
distributionFor
Indicates a relationship where one entity serves as the distribution, delivery, or dissemination mechanism for another entity.
-
B.
distributesIn
Indicates that one entity allocates or hands out something (e.g., items, resources, information) within or across a specified area, group, or context.
-
C.
distributesFrom
Indicates that something acts as the source or origin from which items, resources, or information are distributed to others.
-
D.
targetDistribution
Indicates the intended allocation or spread of something (such as resources, data, or outputs) across specified targets or recipients.
-
E.
distributionByCountry
Indicates how something is allocated, spread, or categorized according to different countries.
- 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_69e7ab38086081908f3a8e7e0c6efd83 |
completed | April 21, 2026, 4:52 p.m. |
| NER | Named-entity recognition | batch_69f601f80b9c8190947c4542654455a6 |
completed | May 2, 2026, 1:54 p.m. |
| PD | Predicate disambiguation | batch_69f4a0fed15881909b789251fe5d8d45 |
completed | May 1, 2026, 12:47 p.m. |
| PDg | Predicate description generation | batch_69f55e497fa081909bc59a7b92c5df59 |
completed | May 2, 2026, 2:15 a.m. |
Created at: April 22, 2026, 7:49 a.m.