Triple
T35013430
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Haven |
E1009990
|
entity |
| Predicate | hasDefenseType |
P195046
|
FINISHED |
| Object | city walls and guards |
—
|
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: city walls and guards | Statement: [Haven, hasDefenseType, city walls and guards]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: hasDefenseType Context triple: [Haven, hasDefenseType, city walls and guards]
-
A.
hasDefensiveType
chosen
Indicates that an entity possesses or is associated with a particular defensive category, attribute, or capability used for protection.
-
B.
hasDefenseStrategy
Indicates that an entity employs or is associated with a particular plan or set of measures designed to protect against threats or attacks.
-
C.
hasBaseDefense
Indicates that an entity possesses a specified level or value of defensive capability in its default or starting state.
-
D.
typeOfDefense
Indicates the specific kind or category of defense employed or possessed in a given context.
-
E.
shipDefenseType
Indicates the specific kind of defensive system or protection mechanism that a ship employs.
- 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_69f76dcc3ac8819096a3ed52f5fa2523 |
completed | May 3, 2026, 3:46 p.m. |
| NER | Named-entity recognition | batch_69ff370698ec81909bb1596d7d4112ba |
completed | May 9, 2026, 1:30 p.m. |
| PD | Predicate disambiguation | batch_69ff3699b6288190b564839cb05f5cf6 |
completed | May 9, 2026, 1:28 p.m. |
Created at: May 3, 2026, 4:01 p.m.