Triple
T16035539
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Tehanu |
E388960
|
entity |
| Predicate | focusesOn |
P31
|
FINISHED |
| Object |
a traumatized child named Therru
Therru is a deeply scarred, withdrawn young girl in Ursula K. Le Guin’s Earthsea cycle whose past abuse and mysterious inner power make her central to the later novels’ exploration of trauma and healing.
|
E1190622
|
NE FINISHED |
How this triple was built (4 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: a traumatized child named Therru | Statement: [Tehanu, focusesOn, a traumatized child named Therru]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: a traumatized child named Therru Context triple: [Tehanu, focusesOn, a traumatized child named Therru]
-
A.
Threst
Threst is a minor character appearing in the Doctor Who serial "Attack of the Cybermen."
-
B.
Thurio
Thurio is a foolish and cowardly nobleman in Shakespeare’s comedy "The Two Gentlemen of Verona," presented as an unworthy suitor to Silvia.
-
C.
Thel
Thel is a shortened given name or nickname derived from the name Thelma.
-
D.
Torey
Torey is a given name, typically used as a variant of names like Tore or Tory.
-
E.
Terri
Terri is a supporting character in the comedy film "Beauty Shop," contributing to the ensemble of stylists and clients at the salon.
- F. None of above. chosen
- G. Unsure - the case is ambiguous/there is not enough information to decide.
NEDg
Description generation
gpt-5.1
Instruction
Generate a one-sentence description of the target entity. You are given a context triple in the form (subject, predicate, object), where the object is the target entity. # Instructions Use the triple to infer relevant information about the entity. Describe the entity based on what is most defining, well-known. Avoid repeating the information from the triple, unless really essential. # Response Format Return only the sentence: "Description: [one-sentence description of the target entity]"
Input
Entity: a traumatized child named Therru Triple: [Tehanu, focusesOn, a traumatized child named Therru]
Generated description
Therru is a deeply scarred, withdrawn young girl in Ursula K. Le Guin’s Earthsea cycle whose past abuse and mysterious inner power make her central to the later novels’ exploration of trauma and healing.
NED2
Entity disambiguation (via description)
gpt-5-mini-2025-08-07
Target entity: a traumatized child named Therru Target entity description: Therru is a deeply scarred, withdrawn young girl in Ursula K. Le Guin’s Earthsea cycle whose past abuse and mysterious inner power make her central to the later novels’ exploration of trauma and healing.
-
A.
Threst
Threst is a minor character appearing in the Doctor Who serial "Attack of the Cybermen."
-
B.
Thurio
Thurio is a foolish and cowardly nobleman in Shakespeare’s comedy "The Two Gentlemen of Verona," presented as an unworthy suitor to Silvia.
-
C.
Thel
Thel is a shortened given name or nickname derived from the name Thelma.
-
D.
Torey
Torey is a given name, typically used as a variant of names like Tore or Tory.
-
E.
Terri
Terri is a common diminutive form of the given name Theresa.
- F. None of above. chosen
Provenance (5 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_69d86dada3808190825d5f80d72fbe88 |
completed | April 10, 2026, 3:25 a.m. |
| NER | Named-entity recognition | batch_69e1833b84608190887dafda5d081dc0 |
completed | April 17, 2026, 12:47 a.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69ffdbd3a1248190ad055892cebde5f0 |
completed | May 10, 2026, 1:13 a.m. |
| NEDg | Description generation | batch_69ffdc5fd30c8190aaf66482f24285b4 |
completed | May 10, 2026, 1:16 a.m. |
| NED2 | Entity disambiguation (via description) | batch_69ffdd0392e08190af42a0cdc5dd4c1f |
completed | May 10, 2026, 1:18 a.m. |
Created at: April 10, 2026, 4:56 a.m.