Triple
T16532475
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Lamanai |
E401600
|
entity |
| Predicate | continuousOccupationDuration |
P66009
|
FINISHED |
| Object | over 3,000 years |
—
|
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: over 3,000 years | Statement: [Lamanai, continuousOccupationDuration, over 3,000 years]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: continuousOccupationDuration Context triple: [Lamanai, continuousOccupationDuration, over 3,000 years]
-
A.
occupationDuration
Indicates the length of time an entity holds or has held a particular occupation or role.
-
B.
jointOccupationDuration
Indicates the length of time that two or more entities simultaneously share the same occupation or role.
-
C.
locationPeriod
Indicates that an entity is associated with being at a particular location during a specified time period.
-
D.
continuousHumanPresenceSince
chosen
Indicates that there has been an unbroken, ongoing human presence at or associated with the subject entity since the specified point in time.
-
E.
durationTotal
Indicates the overall length of time for which an event, process, or state persists, typically aggregating all its constituent durations.
- 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_69d883838abc8190bc79cb2d41733ce2 |
completed | April 10, 2026, 4:58 a.m. |
| NER | Named-entity recognition | batch_69e32ed97b0881909de106418aca8180 |
completed | April 18, 2026, 7:12 a.m. |
| PD | Predicate disambiguation | batch_69e2969fab208190ad64164d24748c45 |
completed | April 17, 2026, 8:22 p.m. |
Created at: April 10, 2026, 5:15 a.m.