Triple
T29655160
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Dark Archon |
E750243
|
entity |
| Predicate | hasHitPoints |
P138109
|
FINISHED |
| Object | true |
—
|
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: true | Statement: [Dark Archon, hasHitPoints, true]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasHitPoints Context triple: [Dark Archon, hasHitPoints, true]
-
A.
hitPointsType
Indicates the category or nature of hit points an entity uses (e.g., health, shield, or other durability type) in the relationship or system.
-
B.
hasBaseHP
chosen
Indicates that an entity possesses a specified amount of base hit points (HP) as its fundamental health value.
-
C.
hasNotableHit
Indicates that an entity is associated with a particularly successful, famous, or widely recognized work, performance, or achievement.
-
D.
healthPointsJava
Indicates the number of health points an entity has within a Java-based context or implementation.
-
E.
hasApproximateNumberOfWounds
Indicates that an entity has a number of wounds that is known only approximately rather than as an exact count.
- 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_69f0d6226fe881908819197c9ef9ee04 |
completed | April 28, 2026, 3:45 p.m. |
| NER | Named-entity recognition | batch_69fd68abf52881909c5a390c362b7c59 |
completed | May 8, 2026, 4:38 a.m. |
| PD | Predicate disambiguation | batch_69fd6812d0c88190930d8fa2d4b92490 |
completed | May 8, 2026, 4:35 a.m. |
Created at: April 28, 2026, 6:54 p.m.