Triple
T23151247
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Kalingapatnam |
E578327
|
entity |
| Predicate | maritimeHistory |
P20564
|
FINISHED |
| Object | linked to Kalinga sea trade routes |
—
|
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: linked to Kalinga sea trade routes | Statement: [Kalingapatnam, maritimeHistory, linked to Kalinga sea trade routes]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: maritimeHistory Context triple: [Kalingapatnam, maritimeHistory, linked to Kalinga sea trade routes]
-
A.
navalHistory
Indicates a relationship where an entity is associated with the study, record, or events of naval or maritime military history.
-
B.
hasMaritimeHeritage
chosen
Indicates that an entity possesses a historical, cultural, or traditional connection to maritime activities, seafaring, or the sea.
-
C.
maritimeExpansion
Indicates the process by which an entity extends its influence, activities, or control over new maritime areas, routes, or territories.
-
D.
seaVoyages
Indicates that one entity undertakes or is associated with journeys or travel by sea to or involving another entity.
-
E.
navalEra
Indicates the historical period or era in which a naval-related event, activity, or condition takes place.
- 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_69e245fb8de081908f0eba7b5fd75bc4 |
completed | April 17, 2026, 2:38 p.m. |
| NER | Named-entity recognition | batch_69f18ef982488190984a6358bdcd577c |
completed | April 29, 2026, 4:54 a.m. |
| PD | Predicate disambiguation | batch_69ef89f83b108190aaaa1db6221fc163 |
completed | April 27, 2026, 4:08 p.m. |
Created at: April 17, 2026, 4:01 p.m.