Triple
T4732099
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Al-Masudi |
E105032
|
entity |
| Predicate | travelActivity |
P49970
|
FINISHED |
| Object | traveled widely across the Islamic world |
—
|
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: traveled widely across the Islamic world | Statement: [Al-Masudi, travelActivity, traveled widely across the Islamic world]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: travelActivity Context triple: [Al-Masudi, travelActivity, traveled widely across the Islamic world]
-
A.
touringActivity
Indicates an activity where an entity travels from place to place, typically for visiting, performing, or sightseeing purposes.
-
B.
journeyDestination
Indicates that one entity serves as the endpoint or intended destination of another entity’s journey or travel.
-
C.
coTraveler
Indicates that two or more entities are traveling together along (part of) the same journey or route.
-
D.
travelsOn
Indicates that an entity moves or journeys using a particular route, path, or mode of transportation.
-
E.
travelers
chosen
Indicates that one or more entities are engaged in the activity or role of traveling, typically moving from one place to another.
- 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_69bd43ee52048190b81a4f066534ffb3 |
completed | March 20, 2026, 12:56 p.m. |
| NER | Named-entity recognition | batch_69bd67c9c3c08190a6c4944cdd1362a8 |
completed | March 20, 2026, 3:29 p.m. |
| PD | Predicate disambiguation | batch_69bd6220071881909670c89d072ffb6d |
completed | March 20, 2026, 3:05 p.m. |
Created at: March 20, 2026, 1:19 p.m.