Triple
T19459411
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Eiao |
E486826
|
entity |
| Predicate | hasFormerHumanPresence |
P8341
|
FINISHED |
| Object | archaeological remains |
—
|
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: archaeological remains | Statement: [Eiao, hasFormerHumanPresence, archaeological remains]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasFormerHumanPresence Context triple: [Eiao, hasFormerHumanPresence, archaeological remains]
-
A.
hasHumanPresence
Indicates that humans are physically present in or occupying a given location, object, or context.
-
B.
continuousHumanPresenceSince
Indicates that there has been an unbroken, ongoing human presence at or associated with the subject entity since the specified point in time.
-
C.
historicalPresence
chosen
Indicates that an entity existed, was active, or had a notable presence in a particular place or context during a past time period.
-
D.
airPresence
Indicates that air is present in or around an entity, typically signifying that the entity contains, is surrounded by, or is exposed to air.
-
E.
hasCharacterPresence
Indicates that a particular character appears or is present within a specified context, such as a scene, work, or medium.
- 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_69d8e8d86d608190bd199a98d0297f27 |
completed | April 10, 2026, 12:11 p.m. |
| NER | Named-entity recognition | batch_69e633c6c55c8190965ada884f17c800 |
completed | April 20, 2026, 2:10 p.m. |
| PD | Predicate disambiguation | batch_69e4fd7499a4819082bec0be8afba35c |
completed | April 19, 2026, 4:06 p.m. |
Created at: April 10, 2026, 1:38 p.m.