Triple
T8992167
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Gordon Relief Expedition |
E214815
|
entity |
| Predicate | timeToReachNearKhartoum |
P86205
|
FINISHED |
| Object | January 1885 |
—
|
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: January 1885 | Statement: [Gordon Relief Expedition, timeToReachNearKhartoum, January 1885]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: timeToReachNearKhartoum Context triple: [Gordon Relief Expedition, timeToReachNearKhartoum, January 1885]
-
A.
distanceToCairo_km
Indicates the physical distance, measured in kilometers, between a given entity’s location and the city of Cairo.
-
B.
distanceToTobrukApprox
Indicates an approximate measure of the distance between a given location and Tobruk.
-
C.
distanceToKinshasa
Indicates the measured spatial distance between a given entity’s location and the city of Kinshasa.
-
D.
travelTimeMeccaMedina
Indicates the duration or time required to travel between Mecca and Medina.
-
E.
distanceFromCairo
Indicates the measured spatial distance between a given entity’s location and the city of Cairo.
- 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_69ca83a05c608190bdfdbdb25e994b39 |
completed | March 30, 2026, 2:07 p.m. |
| NER | Named-entity recognition | batch_69cc68753590819094fd70ed35d8cedf |
completed | April 1, 2026, 12:36 a.m. |
| PD | Predicate disambiguation | batch_69cc5edba0f88190b97401636a076d7a |
completed | March 31, 2026, 11:55 p.m. |
| PDg | Predicate description generation | batch_69cc5febd0a08190b2de6fb422343001 |
completed | March 31, 2026, 11:59 p.m. |
Created at: March 30, 2026, 7:04 p.m.