Triple
T2456795
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Aragonese Crusade |
E54439
|
entity |
| Predicate | hasChronologicalContext |
P1409
|
FINISHED |
| Object | late 13th century |
—
|
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: late 13th century | Statement: [Aragonese Crusade, hasChronologicalContext, late 13th century]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasChronologicalContext Context triple: [Aragonese Crusade, hasChronologicalContext, late 13th century]
-
A.
hasHistoricalContext
chosen
Indicates that something is related to, influenced by, or best understood in light of specific past events, conditions, or time periods.
-
B.
chronologicallyCovers
Indicates that one time period, event, or sequence extends over and includes the entire chronological span of another.
-
C.
chronologicallyAfter
Indicates that one event or state occurs later in time than another.
-
D.
chronologicalFunction
Indicates a temporal relationship where one event or state functions to order, structure, or position another within a sequence of time.
-
E.
chronologicalPosition
Indicates the relative ordering of one event or entity in time with respect 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_69ab49dee84c819096b50a0049c347ac |
completed | March 6, 2026, 9:40 p.m. |
| NER | Named-entity recognition | batch_69abd49c5aa081909ab4f726a458b77f |
completed | March 7, 2026, 7:32 a.m. |
| PD | Predicate disambiguation | batch_69abd0b199488190aa381b36593ae1ac |
completed | March 7, 2026, 7:16 a.m. |
Created at: March 6, 2026, 9:44 p.m.