Triple
T15676057
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Louis the Lion |
E377446
|
entity |
| Predicate | attemptedTitle |
P119724
|
FINISHED |
| Object | King of England |
—
|
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: King of England | Statement: [Louis the Lion, attemptedTitle, King of England]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: attemptedTitle Context triple: [Louis the Lion, attemptedTitle, King of England]
-
A.
aimedTitle
Indicates that one entity is the intended or targeted title or heading associated with another entity.
-
B.
hadTitle
Indicates that an entity held or was assigned a specific title or formal designation.
-
C.
alternateWorkingTitle
Indicates that one title serves as an alternative working title for the same work or project as another title.
-
D.
claimedTitle
Indicates that an entity asserts or declares possession of a particular title or rank.
-
E.
titleThrough
Indicates a relationship where one entity holds or is identified by a specific title by means of, or via the mediation of, another entity or context.
- 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_69d85cd2e28481909d4e975bee20872f |
completed | April 10, 2026, 2:13 a.m. |
| NER | Named-entity recognition | batch_69e04f2e10a4819097eba1ea31e36ac2 |
completed | April 16, 2026, 2:53 a.m. |
| PD | Predicate disambiguation | batch_69deda8b36a4819081cb5708fe77ef51 |
completed | April 15, 2026, 12:23 a.m. |
| PDg | Predicate description generation | batch_69dff7f3016c8190ac68d76e65e07af4 |
completed | April 15, 2026, 8:41 p.m. |
Created at: April 10, 2026, 4:16 a.m.